├── .gitignore ├── LICENSE ├── README.md ├── common.h ├── exercise2-matrices-operations ├── CMakeLists.txt └── example.cpp ├── exercise3-rotations ├── CMakeLists.txt ├── example.cpp └── rotations.cpp ├── exercise4-undistorted-reprojection-and-projections ├── 3dto2dprojections.cpp ├── CMakeLists.txt ├── img1.jpg ├── img2.jpg ├── json.hpp └── radial-distortion.cpp ├── exercise5-harris-corner-detector ├── CMakeLists.txt ├── harris-corner-detector-fine.cpp └── harris-corner-detector.cpp ├── exercise6-eight-point-algorithm ├── AKAZE_match.cpp ├── CMakeLists.txt ├── eight-point-algorithm-matlab-solution.cpp └── eight-point-algorithm.cpp ├── exercise7-direct-methods-1 ├── CMakeLists.txt ├── depth │ ├── 1305031102.160407.png │ ├── 1305031102.262886.png │ ├── 1341847980.723020.png │ └── 1341847982.998830.png ├── direct-methods.cpp └── rgb │ ├── 1305031102.175304.png │ ├── 1305031102.275326.png │ ├── 1341847980.722988.png │ └── 1341847982.998783.png ├── exercise8-epipolarLines ├── CMakeLists.txt └── epipolar-line.cpp └── exercise9-dirct-methods-2 ├── CMakeLists.txt ├── depth ├── 1305031102.160407.png ├── 1305031102.262886.png ├── 1341847980.723020.png └── 1341847982.998830.png ├── direct-methods.cpp └── rgb ├── 1305031102.175304.png ├── 1305031102.275326.png ├── 1341847980.722988.png └── 1341847982.998783.png /.gitignore: -------------------------------------------------------------------------------- 1 | # Prerequisites 2 | *.d 3 | 4 | # Compiled Object files 5 | *.slo 6 | *.lo 7 | *.o 8 | *.obj 9 | 10 | # Precompiled Headers 11 | *.gch 12 | *.pch 13 | 14 | # Compiled Dynamic libraries 15 | *.so 16 | *.dylib 17 | *.dll 18 | 19 | # Fortran module files 20 | *.mod 21 | *.smod 22 | 23 | # Compiled Static libraries 24 | *.lai 25 | *.la 26 | *.a 27 | *.lib 28 | 29 | # Executables 30 | *.exe 31 | *.out 32 | *.app 33 | 34 | # Custom 35 | *build* 36 | 37 | #Vim 38 | *.swp 39 | *.vim 40 | *tags* 41 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | {one line to give the program's name and a brief idea of what it does.} 635 | Copyright (C) {year} {name of author} 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | {project} Copyright (C) {year} {fullname} 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Multiple view geometry exercises. 2 | 3 | 4 | For now - these are badly written solutions to exercises from this course. 5 | https://www.youtube.com/watch?v=RDkwklFGMfo&list=PLTBdjV_4f-EJn6udZ34tht9EVIW7lbeo4 6 | 7 | I'll be improving them and explaining some MVG concepts in my own youtube series. 8 | 9 | 10 | License is GPLv3 due to stupid reasons. If you want them under any other license, you can email me and get them for free, no worries. 11 | 12 | lyubomir(dot)dinchev(that email symbol)gmail 13 | -------------------------------------------------------------------------------- /common.h: -------------------------------------------------------------------------------- 1 | #include 2 | using namespace std; 3 | using namespace cv; 4 | 5 | 6 | 7 | Mat pointToMat(Point2f point) { 8 | float arr[] = {point.x, point.y, 1}; 9 | cv::Mat mat = Mat(3, 1, CV_32F, arr); 10 | return mat.clone(); 11 | } 12 | // A = [0 -v(3) v(2) ; v(3) 0 -v(1) ; -v(2) v(1) 0]; 13 | 14 | string type2str(int type) { 15 | string r; 16 | 17 | uchar depth = type & CV_MAT_DEPTH_MASK; 18 | uchar chans = 1 + (type >> CV_CN_SHIFT); 19 | 20 | switch ( depth ) { 21 | case CV_8U: r = "8U"; break; 22 | case CV_8S: r = "8S"; break; 23 | case CV_16U: r = "16U"; break; 24 | case CV_16S: r = "16S"; break; 25 | case CV_32S: r = "32S"; break; 26 | case CV_32F: r = "32F"; break; 27 | case CV_64F: r = "64F"; break; 28 | default: r = "User"; break; 29 | } 30 | 31 | r += "C"; 32 | r += (chans+'0'); 33 | 34 | return r; 35 | } 36 | 37 | void printType(Mat m) { 38 | cout < points, Mat& res) { 42 | res = img.clone(); 43 | for (int i=0;i< points.size();i++) { 44 | circle( res, 45 | points[i], 46 | 2.0, 47 | Scalar( 0, 0, 255 )); 48 | } 49 | } 50 | 51 | void printVector(vector v) { 52 | 53 | for(int i=0;i v) { 59 | 60 | for(int i=0;i(row++,0) = u.at(i, 0) * v.at(j, 0); 77 | } 78 | } 79 | return res.clone(); 80 | } 81 | 82 | void printMat(Mat m) { 83 | cout << m.rows << "x" << m.cols << " " << type2str(m.type()).c_str() << endl; 84 | cout << m << endl << endl; 85 | } 86 | 87 | Mat transpose(Mat m) { 88 | Mat mt; 89 | transpose(m, mt); 90 | return mt.clone(); 91 | } 92 | 93 | 94 | Mat se3Exp(Mat_ twist) { 95 | float r[] = {twist(0,3), twist(0,4), twist(0, 5)}; 96 | 97 | Mat_ R; 98 | Rodrigues(Mat(3,1,CV_32F, r), R); 99 | 100 | float M[] = {0, 0, 0, twist(0,0), 101 | 0, 0, 0, twist(0,1), 102 | 0, 0, 0, twist(0,2), 103 | 0, 0, 0, 1}; 104 | 105 | Mat_ T = Mat(4,4,CV_32F, M); 106 | R.copyTo(T(cv::Rect(0,0,3,3))); 107 | return T.clone(); 108 | } 109 | 110 | Mat se3Log(Mat_ T) { 111 | 112 | Mat_ twist = Mat::zeros(1,6, CV_32F); 113 | twist(0,0) = T(0,3); 114 | twist(0,1) = T(1,3); 115 | twist(0,2) = T(2,3); 116 | 117 | Mat_ R; 118 | Rodrigues(T(Rect(0,0,3,3)), R); 119 | twist(0,3) = R(0,0); 120 | twist(0,4) = R(1,0); 121 | twist(0,5) = R(2,0); 122 | 123 | return twist.clone(); 124 | } 125 | 126 | void downscaleK(Mat_ &K, int num) { 127 | if(num<=1) { 128 | return; 129 | } 130 | 131 | // this is because we interpolate in such a way, that 132 | // the image is discretized at the exact pixel-values (e.g. 3,7), and 133 | // not at the center of each pixel (e.g. 3.5, 7.5). 134 | K(0,0) = (float)K(0,0)/2.0; 135 | K(0,1) = 0; 136 | K(0,2) = (float)(K(0,2)+0.5)/2.0-0.5; 137 | 138 | K(1,0) = 0; 139 | K(1,1) = (float)K(1,1)/2.0; 140 | K(1,2) = (float)(K(1,2)+0.5)/2.0-0.5; 141 | downscaleK(K, num-1); 142 | } 143 | 144 | template 145 | void downscaleImage(Mat &image, int num) { 146 | if(num<=1) { 147 | return; 148 | } 149 | Mat smaller_image = Mat(image.rows/2,image.cols/2, CV_32F); 150 | 151 | for (int i=0; i(i,j) = (T) (( image.at(2*i,2*j) + 154 | image.at(2*i+1,2*j) + 155 | image.at(2*i,2*j+1) + 156 | image.at(2*i+1,2*j+1))*0.25); 157 | } 158 | } 159 | 160 | image = smaller_image.clone(); 161 | downscaleImage(image, num -1 ); 162 | } 163 | template 164 | void upscaleImage(Mat &image, int num) { 165 | if(num<=1) { 166 | return; 167 | } 168 | Mat bigger_image = Mat_(image.rows*2,image.cols*2); 169 | 170 | for (int i=0; i(i,j) = (T) image.at(i/2,j/2); 173 | } 174 | } 175 | 176 | image = bigger_image.clone(); 177 | upscaleImage(image, num -1 ); 178 | } 179 | 180 | template 181 | void downscaleDepth(Mat& image, int num){ 182 | 183 | if(num<=1) { 184 | return; 185 | } 186 | 187 | Mat smaller = Mat_(image.rows/2,image.cols/2); 188 | for (int i=0; i(2*i,2*j) > 0) + 191 | (int)(image.at(2*i+1,2*j) > 0) + 192 | (int)(image.at(2*i,2*j+1) > 0) + 193 | (int)(image.at(2*i+1,2*j+1) > 0); 194 | 195 | 196 | if (denominator > 0) { 197 | smaller.at(i,j) = (T)(( image.at(2*i,2*j) + 198 | image.at(2*i+1,2*j) + 199 | image.at(2*i,2*j+1) + 200 | image.at(2*i+1,2*j+1))/denominator); 201 | } else { 202 | smaller.at(i,j) = 0; 203 | } 204 | } 205 | } 206 | image = smaller.clone(); 207 | downscaleDepth( image, num -1 ); 208 | } 209 | 210 | template 211 | void calculateGradients(Mat_ image, Mat_& Idrow, Mat_& Idcol) { 212 | 213 | /* Mat Ix_temp, Iy_temp; 214 | 215 | Idrow = Mat_(image.rows, image.cols); 216 | Idcol = Mat_(image.rows, image.cols); 217 | 218 | Sobel( image, Ix_temp, CV_32F, 1, 0, 3, 1, 0, BORDER_DEFAULT ); 219 | Sobel( image, Iy_temp, CV_32F, 0, 1, 3, 1, 0, BORDER_DEFAULT ); 220 | //convertScaleAbs(Ix_temp, Ix); 221 | //convertScaleAbs(Iy_temp, Iy); 222 | Idrow = Ix_temp; 223 | Idcol = Iy_temp;*/ 224 | 225 | Idrow = Mat_(image.rows, image.cols,(T)0); 226 | Idcol = Mat_(image.rows, image.cols, (T)0); 227 | //Ixy = Mat_(image.rows, image.cols); 228 | 229 | for (int row=1; row 243 | cv::Mat_ hat(Mat_ vec) { 244 | T skew[] = { 245 | 0, -vec(2,0), vec(1,0), 246 | vec(2,0), 0, -vec(0,0), 247 | -vec(1,0), vec(0,0), 0}; 248 | 249 | cv::Mat_ skewMat = Mat_(3, 3, skew); 250 | return skewMat.clone(); 251 | } 252 | 253 | cv::Point3f MPoint3fMult(cv::Mat M, const cv::Point3f& p) 254 | { 255 | cv::Mat_ src(4/*rows*/,1 /* cols */); 256 | 257 | src(0,0)=p.x; 258 | src(1,0)=p.y; 259 | src(2,0)=p.z; 260 | src(3,0)=1.0; 261 | 262 | cv::Mat_ dst = M*src; //USE MATRIX ALGEBRA 263 | return cv::Point3f(dst(0,0), dst(1,0), dst(2,0)); 264 | } 265 | -------------------------------------------------------------------------------- /exercise2-matrices-operations/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 22 | # Add OpenCV headers location to your include paths 23 | include_directories(${OpenCV_INCLUDE_DIRS}) 24 | endif() 25 | 26 | # Declare the executable target built from your sources 27 | add_executable(opencv_example example.cpp) 28 | 29 | # Link your application with OpenCV libraries 30 | target_link_libraries(opencv_example ${OpenCV_LIBS}) 31 | -------------------------------------------------------------------------------- /exercise2-matrices-operations/example.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include "opencv2/core.hpp" 3 | 4 | using namespace cv; 5 | using namespace std; 6 | 7 | int main() 8 | { 9 | cout << "Built with OpenCV " << CV_VERSION << endl; 10 | float val[] = {2,6,7,8,5, 11 | 6,9,6,8,5, 12 | 7,6,1,7,5, 13 | 8,8,7,12,5, 14 | 5,5,5,5,5}; 15 | float val2[] = {2,6,7,8,5, 16 | 6,9,6,8,5, 17 | 7,6,1,7,5, 18 | 8,8,7,12,5, 19 | 5,5,5,5,0}; 20 | float val3[] = {1,2,3,4,5}; 21 | 22 | Mat mat1 = Mat(5,5, CV_32F, val); 23 | Mat mat2 = Mat(5,5, CV_32F, val2); 24 | Mat b = Mat(5,1, CV_32F, val3); 25 | // cout << mat1 << endl; 26 | cout << mat1.inv()*b << endl; 27 | // cout << mat2 << endl; 28 | cout << mat2.inv(DECOMP_SVD)*b << endl; 29 | 30 | // Mat eigenVal, eigenVec; 31 | 32 | // eigen(mat1, eigenVal, eigenVec); 33 | 34 | // cout << eigenVal << eigenVec; 35 | // cout << "--------\n"; 36 | // eigen(mat2, eigenVal, eigenVec); 37 | 38 | // cout << eigenVal << eigenVec; 39 | 40 | // SVD svd = SVD(mat1); 41 | 42 | //icout << Mat::diag(svd.w) << endl; 43 | // cout << mat1 << endl; 44 | // cout << svd.u*Mat::diag(svd.w)*svd.vt << endl; 45 | 46 | return 0; 47 | 48 | -------------------------------------------------------------------------------- /exercise3-rotations/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | set(CMAKE_CXX_FLAGS "-O3 -pg ") 13 | SET(CMAKE_CXX_COMPILER /usr/bin/g++) 14 | 15 | 16 | 17 | # If the package has been found, several variables will 18 | # be set, you can find the full list with descriptions 19 | # in the OpenCVConfig.cmake file. 20 | # Print some message showing some of them 21 | message(STATUS "OpenCV library status:") 22 | message(STATUS " version: ${OpenCV_VERSION}") 23 | message(STATUS " libraries: ${OpenCV_LIBS}") 24 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 25 | 26 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 27 | # Add OpenCV headers location to your include paths 28 | include_directories(${OpenCV_INCLUDE_DIRS}) 29 | endif() 30 | 31 | # Declare the executable target built from your sources 32 | add_executable(opencv_example example.cpp) 33 | 34 | # Link your application with OpenCV libraries 35 | target_link_libraries(opencv_example ${OpenCV_LIBS}) 36 | 37 | # Declare the executable target built from your sources 38 | add_executable(rotations rotations.cpp) 39 | 40 | # Link your application with OpenCV libraries 41 | target_link_libraries(rotations ${OpenCV_LIBS}) 42 | -------------------------------------------------------------------------------- /exercise3-rotations/example.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "opencv2/core.hpp" 4 | #include "opencv2/viz.hpp" 5 | 6 | using namespace cv; 7 | using namespace std; 8 | 9 | 10 | cv::Point3f mult(cv::Point3f& p, cv::Mat M) 11 | { 12 | cv::Mat_ src(4,1 ); 13 | 14 | src(0,0)=p.x; 15 | src(1,0)=p.y; 16 | src(2,0)=p.z; 17 | src(3,0) = 1; 18 | 19 | cv::Mat_ dst = M*src; //USE MATRIX ALGEBRA 20 | //printf("%f %f %f, %f %f %f\n", p.x, p.y, p.z, dst(0,0), dst(0,1), dst(0,2)); 21 | return cv::Point3f(dst(0,0),dst(1,0), dst(2,0)); 22 | } 23 | void applyMat(Mat m, vector &vec) { 24 | for (int i=0; i< vec.size(); i++) { 25 | vec[i] = mult(vec[i], m); 26 | // vec[i].x++; 27 | 28 | } 29 | } 30 | 31 | cv::Mat hat(cv::Mat_ vec) { 32 | float skew[] = { 33 | 0, -vec(2,0),vec(1,0), 34 | vec(2,0),0,vec(0,0), 35 | -vec(1,0),vec(0,0),0}; 36 | cv::Mat skewMat = Mat(3, 3, CV_32F, skew); 37 | return skewMat.clone(); 38 | } 39 | 40 | cv::Mat vecToRotationMat(cv::Mat_ vec) { 41 | float one[] = {1,0,0, 42 | 0,1,0, 43 | 0,0,1}; 44 | cv::Mat I = cv::Mat(3,3, CV_32F, one); 45 | cv::Mat vecHat = hat(vec); 46 | 47 | float metricVec = sqrt( vec(0,0)*vec(0,0) + vec(1,0)*vec(1,0) + vec(2,0)*vec(2,0)) ; 48 | //cout << "metric: " << metricVec << endl; 49 | cv::Mat result = I + (vecHat/metricVec)*sin(metricVec) + (vecHat)*(vecHat)/(metricVec*metricVec)*(1-cos(metricVec)); 50 | return result.clone(); 51 | } 52 | 53 | cv::Mat rotationToVec(cv::Mat_ mat) { 54 | float length_w = acos((trace(mat)[0]-1)/2); 55 | float helper[] = {mat(2,1)-mat(2,1), mat(0,2)-mat(2,0), mat(1,0)-mat(0,1)}; 56 | Mat helper_mat = cv::Mat(3,1, CV_32F, helper); 57 | cout << "helper: " << helper_mat << endl; 58 | Mat w; 59 | w = 1/(2*sin(length_w))*helper_mat*length_w; 60 | return w; 61 | } 62 | 63 | int main() 64 | { 65 | cout << "Built with OpenCV " << CV_VERSION << endl; 66 | /////////////// 67 | float skew[] = { 68 | 1, 1, 1 }; 69 | cv::Mat vec = Mat(3,1, CV_32F, skew); 70 | cout << vecToRotationMat(vec) << endl; 71 | cout << rotationToVec(vecToRotationMat(vec)); 72 | return 0; 73 | /////////////// 74 | FILE* points_file; 75 | points_file = fopen("model.off", "r"); 76 | int points_count, triangles_count, zero; 77 | float m_x = 0, m_z = 0, m_y = 0; 78 | fscanf(points_file, "%d %d %d", &points_count, &triangles_count, &zero); 79 | vector point_cloud; 80 | vector triangle; 81 | printf("reading points: %d\n", points_count); 82 | viz::Viz3d trajectoryWindow("show"); 83 | float x,y,z; 84 | for (int i=0; i< points_count;i++) { 85 | fscanf(points_file, "%f %f %f", &x, &y, &z); 86 | point_cloud.push_back(Point3f(x,y,z)); 87 | m_x +=x; m_y+=y; m_z+=z; 88 | } 89 | 90 | int d, a, b, c; 91 | for (int i=0; i< triangles_count;i++) { 92 | fscanf(points_file, "%d %d %d %d", &d, &a, &b, &c); 93 | triangle.push_back(d); 94 | triangle.push_back(a); 95 | triangle.push_back(b); 96 | triangle.push_back(c); 97 | } 98 | m_x /= points_count; 99 | m_y /= points_count; 100 | m_z /= points_count; 101 | 102 | viz::WMesh mesh = viz::WMesh(point_cloud, triangle); 103 | trajectoryWindow.showWidget("point_cloud", mesh); 104 | 105 | float translation[] = {1,0,0,-m_x-0.5, 106 | 0,1,0,-m_y-0.2, 107 | 0,0,1,-m_z-0.1, 108 | 0,0,0,1}; 109 | 110 | Mat trans = Mat(4,4, CV_32F, translation); 111 | 112 | float alpha = 3.14/36; 113 | float val_x[] ={ 1, 0, 0, 0, 114 | 0, cos(alpha), -sin(alpha), 0, 115 | 0, sin(alpha), cos(alpha), 0, 116 | 0, 0, 0, 1}; 117 | Mat rot_x = Mat(4,4, CV_32F, val_x ); 118 | float beta = 0/5; 119 | float val_y[] ={ cos(beta), 0, sin(beta), 0, 120 | 0, 1, 0, 0, 121 | -sin(beta), 0, cos(beta), 0, 122 | 0, 0, 0, 1}; 123 | Mat rot_y = Mat(4,4, CV_32F, val_y ); 124 | float gamma = 3.14/7.2;//3.14/6; 125 | float val_z[] ={ cos(gamma), -sin(gamma), 0, 0, 126 | sin(gamma), cos(gamma), 0, 0, 127 | 0, 0, 1, 0, 128 | 0, 0, 0, 1}; 129 | Mat rot_z = Mat(4,4, CV_32F, val_z ); 130 | Mat rot = rot_x*rot_z*rot_y; 131 | printf("meanx: %f\n", m_x); 132 | while (true) { 133 | usleep(50000); 134 | applyMat(trans.inv()*rot*trans, point_cloud); 135 | viz::WMesh mesh2 = viz::WMesh(point_cloud, triangle); 136 | trajectoryWindow.showWidget("point_cloudi2", mesh2); 137 | 138 | trajectoryWindow.spinOnce(); 139 | break; 140 | } 141 | trajectoryWindow.spin(); 142 | return 0; 143 | } 144 | -------------------------------------------------------------------------------- /exercise3-rotations/rotations.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "opencv2/core.hpp" 4 | #include "opencv2/viz.hpp" 5 | 6 | using namespace cv; 7 | using namespace std; 8 | 9 | 10 | cv::Point3f mult(cv::Point3f& p, cv::Mat M) 11 | { 12 | cv::Mat_ src(4/* rows*/,1 /* cols */); 13 | 14 | src(0,0)=p.x; 15 | src(1,0)=p.y; 16 | src(2,0)=p.z; 17 | src(3,0) = 1; 18 | 19 | cv::Mat_ dst = M*src; //USE MATRIX ALGEBRA 20 | //printf("%f %f %f, %f %f %f\n", p.x, p.y, p.z, dst(0,0), dst(0,1), dst(0,2)); 21 | return cv::Point3f(dst(0,0),dst(1,0), dst(2,0)); 22 | } 23 | void applyMat(Mat m, vector &vec) { 24 | for (int i=0; i< vec.size(); i++) { 25 | vec[i] = mult(vec[i], m); 26 | // vec[i].x++; 27 | 28 | } 29 | } 30 | 31 | int main() 32 | { 33 | cout << "Built with OpenCV " << CV_VERSION << endl; 34 | 35 | FILE* points_file; 36 | points_file = fopen("model.off", "r"); 37 | int points_count, triangles_count, zero; 38 | float m_x = 0, m_z = 0, m_y = 0; 39 | fscanf(points_file, "%d %d %d", &points_count, &triangles_count, &zero); 40 | vector point_cloud; 41 | vector triangle; 42 | printf("reading points: %d\n", points_count); 43 | viz::Viz3d trajectoryWindow("show"); 44 | float x,y,z; 45 | for (int i=0; i< points_count;i++) { 46 | fscanf(points_file, "%f %f %f", &x, &y, &z); 47 | point_cloud.push_back(Point3f(x,y,z)); 48 | m_x +=x; m_y+=y; m_z+=z; 49 | } 50 | 51 | int d, a, b, c; 52 | for (int i=0; i< triangles_count;i++) { 53 | fscanf(points_file, "%d %d %d %d", &d, &a, &b, &c); 54 | triangle.push_back(d); 55 | triangle.push_back(a); 56 | triangle.push_back(b); 57 | triangle.push_back(c); 58 | } 59 | m_x /= points_count; 60 | m_y /= points_count; 61 | m_z /= points_count; 62 | 63 | viz::WMesh mesh = viz::WMesh(point_cloud, triangle); 64 | trajectoryWindow.showWidget("point_cloud", mesh); 65 | 66 | float translation[] = {1,0,0,-m_x-0.5, 67 | 0,1,0,-m_y-0.2, 68 | 0,0,1,-m_z-0.1, 69 | 0,0,0,1}; 70 | 71 | Mat trans = Mat(4,4, CV_32F, translation); 72 | 73 | float alpha = 3.14/36; 74 | float val_x[] ={ 1, 0, 0, 0, 75 | 0, cos(alpha), -sin(alpha), 0, 76 | 0, sin(alpha), cos(alpha), 0, 77 | 0, 0, 0, 1}; 78 | Mat rot_x = Mat(4,4, CV_32F, val_x ); 79 | float beta = 0/5; 80 | float val_y[] ={ cos(beta), 0, sin(beta), 0, 81 | 0, 1, 0, 0, 82 | -sin(beta), 0, cos(beta), 0, 83 | 0, 0, 0, 1}; 84 | Mat rot_y = Mat(4,4, CV_32F, val_y ); 85 | float gamma = 3.14/7.2;//3.14/6; 86 | float val_z[] ={ cos(gamma), -sin(gamma), 0, 0, 87 | sin(gamma), cos(gamma), 0, 0, 88 | 0, 0, 1, 0, 89 | 0, 0, 0, 1}; 90 | Mat rot_z = Mat(4,4, CV_32F, val_z ); 91 | Mat rot = rot_x*rot_z*rot_y; 92 | printf("meanx: %f\n", m_x); 93 | while (true) { 94 | usleep(50000); 95 | applyMat(trans.inv()*rot*trans, point_cloud); 96 | viz::WMesh mesh2 = viz::WMesh(point_cloud, triangle); 97 | trajectoryWindow.showWidget("point_cloudi2", mesh2); 98 | 99 | trajectoryWindow.spinOnce(); 100 | break; 101 | } 102 | trajectoryWindow.spin(); 103 | return 0; 104 | } 105 | -------------------------------------------------------------------------------- /exercise4-undistorted-reprojection-and-projections/3dto2dprojections.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "opencv2/core.hpp" 4 | #include "opencv2/viz.hpp" 5 | 6 | using namespace cv; 7 | using namespace std; 8 | 9 | 10 | cv::Point3f mult(cv::Mat a, cv::Mat b) 11 | { 12 | cv::Mat_ dst = b*a; 13 | 14 | //printf("%f %f %f, %f %f %f\n", p.x, p.y, p.z, dst(0,0), dst(0,1), dst(0,2)); 15 | float x = dst(0,0)/dst(2,0); 16 | float y = dst(1,0)/dst(2,0); 17 | return cv::Point3f(x, y, 1);//dst(2,0)); 18 | } 19 | Mat point4(float a, float b, float c, float d) { 20 | cv::Mat_ src(4/* rows*/,1 /* cols */); 21 | 22 | src(0,0)=a; 23 | src(1,0)=b; 24 | src(2,0)=c; 25 | src(3,0)=d; 26 | 27 | return src; 28 | } 29 | void applyMat(Mat m, vector &vec) { 30 | for (int i=0; i< vec.size(); i++) { 31 | vec[i] = m*vec[i]; 32 | } 33 | } 34 | 35 | int main() 36 | { 37 | cout << "Built with OpenCV " << CV_VERSION << endl; 38 | 39 | FILE* points_file; 40 | points_file = fopen("model.off", "r"); 41 | int points_count, triangles_count, zero; 42 | float m_x = 0, m_z = 0, m_y = 0; 43 | fscanf(points_file, "%d %d %d", &points_count, &triangles_count, &zero); 44 | vector point_cloud; 45 | vector triangle; 46 | printf("reading points: %d\n", points_count); 47 | viz::Viz3d trajectoryWindow("show"); 48 | float x,y,z; 49 | for (int i=0; i< points_count;i++) { 50 | fscanf(points_file, "%f %f %f", &x, &y, &z); 51 | Mat homogeneus_point = point4(x, y, z, 1); 52 | point_cloud.push_back( homogeneus_point ); 53 | } 54 | 55 | int d, a, b, c; 56 | for (int i=0; i< triangles_count;i++) { 57 | fscanf(points_file, "%d %d %d %d", &d, &a, &b, &c); 58 | triangle.push_back(d); 59 | triangle.push_back(a); 60 | triangle.push_back(b); 61 | triangle.push_back(c); 62 | } 63 | 64 | float moveToCameraCoordinates[] = { 65 | 1,0,0,0, 66 | 0,1,0,0, 67 | 0,0,1,0, 68 | 0,0,0,1}; 69 | 70 | Mat trans = Mat(4,4, CV_32F, moveToCameraCoordinates); 71 | applyMat(trans, point_cloud); 72 | float f = 1.0; 73 | float k[] = { 74 | f, 0, 0, 0, 75 | 0, f, 0, 0, 76 | 0, 0, 1, 0, 77 | 0, 0, 0, 0}; 78 | Mat K = Mat(4,4, CV_32F, k); 79 | vector points_proj; 80 | for (int i=0; i< point_cloud.size();i++) { 81 | points_proj.push_back(mult(point_cloud[i], K)); 82 | } 83 | 84 | 85 | viz::WCloud cloud_widget = viz::WCloud( points_proj, cv::viz::Color::green() ); 86 | cloud_widget.setRenderingProperty( cv::viz::POINT_SIZE, 2 ); 87 | 88 | trajectoryWindow.showWidget("point_cloud", cloud_widget); 89 | 90 | trajectoryWindow.spin(); 91 | return 0; 92 | } 93 | -------------------------------------------------------------------------------- /exercise4-undistorted-reprojection-and-projections/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 3.12) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "-----------------------") 17 | message(STATUS "CMAKE_CURRENT_LIST_FILE ${CMAKE_CURRENT_LIST_FILE}") 18 | 19 | message(STATUS "CMAKE_CURRENT_LIST_DIR ${CMAKE_CURRENT_LIST_DIR}") 20 | 21 | message(STATUS "CMAKE_CURRENT_LIST_LINE ${CMAKE_CURRENT_LIST_LINE}") 22 | 23 | message(STATUS "CMAKE_CURRENT_SOURCE_DIR ${CMAKE_CURRENT_SOURCE_DIR}") 24 | 25 | message(STATUS "PROJECT_BINARY_DIR ${PROJECT_BINARY_DIR}") 26 | message(STATUS "PROJECT_SOURCE_DIR ${PROJECT_SOURCE_DIR}") 27 | 28 | message(STATUS "CMAKE_INCLUDE_PATH ${CMAKE_INCLUDE_PATH}") 29 | 30 | 31 | message(STATUS "PATH ${PATH}") 32 | message(STATUS "$ ENV{PATH} $ENV{PATH}") 33 | 34 | message(STATUS "CMAKE_SYSTEM_PROCESSOR ${CMAKE_SYSTEM_PROCESSOR}") 35 | 36 | message(STATUS "CMAKE_GENERATOR ${CMAKE_GENERATOR}") 37 | 38 | message(STATUS "CMAKE_INSTALL_PREFIX ${CMAKE_INSTALL_PREFIX}") 39 | 40 | 41 | message(STATUS "-----------------------") 42 | 43 | 44 | message(STATUS "OpenCV library status:") 45 | message(STATUS " version: ${OpenCV_VERSION}") 46 | message(STATUS " libraries: ${OpenCV_LIBS}") 47 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 48 | 49 | #set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 50 | set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -O0 -fprofile-arcs -ftest-coverage") 51 | set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -g -O0 -fprofile-arcs -ftest-coverage") 52 | 53 | 54 | 55 | # Declare the executable target built from your sources 56 | add_executable(radial-distortion radial-distortion.cpp) 57 | 58 | target_link_libraries(radial-distortion ${OpenCV_LIBS}) 59 | 60 | -------------------------------------------------------------------------------- /exercise4-undistorted-reprojection-and-projections/img1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise4-undistorted-reprojection-and-projections/img1.jpg -------------------------------------------------------------------------------- /exercise4-undistorted-reprojection-and-projections/img2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise4-undistorted-reprojection-and-projections/img2.jpg -------------------------------------------------------------------------------- /exercise4-undistorted-reprojection-and-projections/radial-distortion.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include "opencv2/core.hpp" 5 | #include 6 | #include 7 | 8 | using namespace cv; 9 | using namespace std; 10 | 11 | #define IMAGE "/home/smith/Datasets/calibration/maxi-car/20240913165608.jpg" 12 | //#define CALIB_FILE "/home/smith/Datasets/calibration/maxi-car/calib-maxi-car.json" 13 | #define CALIB_FILE "/home/smith/Datasets/calibration/maxi-car/calib-maxi-car-no-dist.json" 14 | 15 | #include "json.hpp" 16 | #include 17 | #include 18 | #include 19 | 20 | using namespace cv; 21 | using namespace std; 22 | 23 | // Function to manually undistort fisheye image and reproject with pinhole camera model 24 | void fisheyeToPinhole(const Mat &fisheyeImage, Mat &pinholeImage, 25 | const Mat &K_fisheye, const Mat &D_fisheye, 26 | const Mat &K_pinhole, const float mirrorOffset, const Size &pinholeSize) { 27 | 28 | pinholeImage = Mat::zeros(pinholeSize, fisheyeImage.type()); 29 | 30 | cout << "pinholeImage rows, cols: " << pinholeImage.rows << " " << pinholeImage.cols << std::endl; 31 | cout << "fisheyeImage rows, cols: " << fisheyeImage.rows << " " << fisheyeImage.cols << std::endl; 32 | 33 | float k1 = D_fisheye.at(0, 0); 34 | float k2 = D_fisheye.at(0, 1); 35 | // float k3 = D_fisheye.at(0, 2); 36 | // float k4 = D_fisheye.at(0, 3); 37 | 38 | float fx_fish = K_fisheye.at(0, 0); 39 | float fy_fish = K_fisheye.at(1, 1); 40 | float cx_fish = K_fisheye.at(0, 2); 41 | float cy_fish = K_fisheye.at(1, 2); 42 | 43 | float fx_pin = K_pinhole.at(0, 0); 44 | float fy_pin = K_pinhole.at(1, 1); 45 | float cx_pin = K_pinhole.at(0, 2); 46 | float cy_pin = K_pinhole.at(1, 2); 47 | 48 | std::cout << "pinholeSize.height " << pinholeSize.height << "\n"; 49 | 50 | for (int piholeRow = 0; piholeRow < pinholeImage.rows; piholeRow++) { 51 | for (int pinholeCol = 0; pinholeCol < pinholeImage.cols; pinholeCol++) { 52 | 53 | /*double x_norm = (pinholeCol - cx_pin) / fx_pin; 54 | double y_norm = (piholeRow - cy_pin) / fy_pin; 55 | double r_norm = sqrt(x_norm * x_norm + y_norm * y_norm); 56 | 57 | // Apply inverse of radial distortion to map back to the fisheye image 58 | double theta = atan(r_norm); 59 | double theta_d = theta * (1 + k1 * pow(theta, 2) + k2 * pow(theta, 4)) ;//+ k3 * pow(theta, 6) + k4 * pow(theta, 8)); 60 | 61 | // Convert back to distorted (fisheye) coordinates 62 | int x_fish = cvRound(fx_fish * x_norm * theta_d / r_norm + cx_fish); 63 | int y_fish = cvRound(fy_fish * y_norm * theta_d / r_norm + cy_fish); 64 | 65 | // Check if the coordinates fall within the fisheye image bounds 66 | if (x_fish >= 0 && x_fish < fisheyeImage.cols && y_fish >= 0 && y_fish < fisheyeImage.rows) { 67 | //printf("%d %d max %d %d\n", x_fish, y_fish, fisheyeImage.cols, fisheyeImage.rows); 68 | // Map the fisheye image pixel to the pinhole image 69 | pinholeImage.at(piholeRow, pinholeCol) = fisheyeImage.at(cvRound(y_fish), cvRound(x_fish)); 70 | }*/ 71 | 72 | float x_tau = (pinholeCol - cx_pin) / fx_pin; 73 | float y_tau = (piholeRow - cy_pin) / fy_pin; 74 | 75 | float coeff = (mirrorOffset + sqrt(1 + (1 - mirrorOffset * mirrorOffset) * (x_tau * x_tau + y_tau + y_tau))) / 76 | (x_tau * x_tau + y_tau + y_tau + 1); 77 | 78 | float x_unproj = coeff * x_tau / (coeff - mirrorOffset); 79 | float y_unproj = coeff * y_tau / (coeff - mirrorOffset); 80 | 81 | int x_fish = cvRound(fx_fish * x_unproj + cx_fish); 82 | int y_fish = cvRound(fy_fish * y_unproj + cy_fish); 83 | if (x_fish >= 0 && x_fish < fisheyeImage.cols && y_fish >= 0 && y_fish < fisheyeImage.rows) { 84 | pinholeImage.at(piholeRow, pinholeCol) = fisheyeImage.at(y_fish, x_fish); 85 | } 86 | } 87 | } 88 | } 89 | 90 | int main() { 91 | // Load the fisheye image 92 | Mat fisheyeImage = imread(IMAGE); 93 | if (fisheyeImage.empty()) { 94 | cout << "Error: Could not load the fisheye image!" << endl; 95 | return -1; 96 | } 97 | 98 | std::ifstream calibrationFileStream(CALIB_FILE); 99 | 100 | nlohmann::json calibrationData = nlohmann::json::parse(calibrationFileStream); 101 | 102 | int calibrationRows = calibrationData["resolution"]["y"]; 103 | int calibrationCols = calibrationData["resolution"]["x"]; 104 | 105 | assert(calibrationCols == fisheyeImage.cols && calibrationRows == fisheyeImage.rows); 106 | 107 | float fx = calibrationData["focal_length"]["x"]; // 700.1441001496614 / rows; 108 | float fy = calibrationData["focal_length"]["y"]; // 713.1370873930887 / cols; 109 | float cx = calibrationData["center_pixel"]["x"]; // 321.5265928650794 / rows; 110 | float cy = calibrationData["center_pixel"]["y"]; // 240.1270406206272 / cols; 111 | 112 | float r0 = calibrationData["radial_distortion"]["r0"]; 113 | float r1 = calibrationData["radial_distortion"]["r1"]; 114 | 115 | float mirrorOffset = calibrationData["mirrorOffset"]; 116 | 117 | Mat K_fisheye = (Mat_(3, 3) << fx, 0.0, cx, 118 | 0.0, fy, cy, 119 | 0.0, 0.0, 1.0); 120 | 121 | Mat D_fisheye = (Mat_(1, 2) << r0, r1); 122 | 123 | Size pinholeSize(fisheyeImage.cols * 1.5, fisheyeImage.rows * 1.5); 124 | 125 | Mat K_pinhole = (Mat_(3, 3) << 200.0, 0.0, pinholeSize.width / 2, 126 | 0.0, 200.0, pinholeSize.height / 2, 127 | 0.0, 0.0, 1.0); 128 | 129 | Mat pinholeImage; 130 | fisheyeToPinhole(fisheyeImage, pinholeImage, K_fisheye, D_fisheye, K_pinhole, mirrorOffset, pinholeSize); 131 | 132 | // Save or display the resulting pinhole projection image 133 | imshow("Fisheye Projection", fisheyeImage); 134 | imshow("Pinhole Projection", pinholeImage); 135 | 136 | waitKey(0); 137 | 138 | return 0; 139 | } 140 | -------------------------------------------------------------------------------- /exercise5-harris-corner-detector/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 22 | 23 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 24 | # Add OpenCV headers location to your include paths 25 | include_directories(${OpenCV_INCLUDE_DIRS}) 26 | endif() 27 | 28 | # Declare the executable target built from your sources 29 | add_executable(opencv_example harris-corner-detector-fine.cpp) 30 | 31 | # Link your application with OpenCV libraries 32 | target_link_libraries(opencv_example ${OpenCV_LIBS}) 33 | -------------------------------------------------------------------------------- /exercise5-harris-corner-detector/harris-corner-detector-fine.cpp: -------------------------------------------------------------------------------- 1 | #include "opencv2/highgui/highgui.hpp" 2 | #include "opencv2/imgproc/imgproc.hpp" 3 | #include 4 | #include 5 | #include 6 | 7 | using namespace cv; 8 | using namespace std; 9 | 10 | /// Global variables 11 | Mat src, src_gray; 12 | int thresh = 100; 13 | int max_thresh = 255; 14 | 15 | char* source_window = "Source image"; 16 | char* corners_window = "Corners detected"; 17 | 18 | /// Function header 19 | void cornerHarris_demo( int, void* ); 20 | 21 | /** @function main */ 22 | int main( int argc, char** argv ) 23 | { 24 | /// Load source image and convert it to gray 25 | src = imread( argv[1], 1 ); 26 | cvtColor( src, src_gray, CV_BGR2GRAY ); 27 | 28 | /// Create a window and a trackbar 29 | namedWindow( source_window, CV_WINDOW_AUTOSIZE ); 30 | createTrackbar( "Threshold: ", source_window, &thresh, max_thresh, cornerHarris_demo ); 31 | imshow( source_window, src ); 32 | 33 | cornerHarris_demo( 0, 0 ); 34 | 35 | waitKey(0); 36 | return(0); 37 | } 38 | 39 | /** @function cornerHarris_demo */ 40 | void cornerHarris_demo( int, void* ) 41 | { 42 | 43 | Mat dst, dst_norm, dst_norm_scaled; 44 | dst = Mat::zeros( src.size(), CV_32FC1 ); 45 | 46 | /// Detector parameters 47 | int blockSize = 2; 48 | int apertureSize = 3; 49 | double k = 0.04; 50 | 51 | /// Detecting corners 52 | cornerHarris( src_gray, dst, blockSize, apertureSize, k, BORDER_DEFAULT ); 53 | 54 | /// Normalizing 55 | normalize( dst, dst_norm, 0, 255, NORM_MINMAX, CV_32FC1, Mat() ); 56 | convertScaleAbs( dst_norm, dst_norm_scaled ); 57 | 58 | /// Drawing a circle around corners 59 | for( int j = 0; j < dst_norm.rows ; j++ ) 60 | { for( int i = 0; i < dst_norm.cols; i++ ) 61 | { 62 | if( (int) dst_norm.at(j,i) > thresh ) 63 | { 64 | circle( dst_norm_scaled, Point( i, j ), 5, Scalar(0), 2, 8, 0 ); 65 | } 66 | } 67 | } 68 | /// Showing the result 69 | namedWindow( corners_window, CV_WINDOW_AUTOSIZE ); 70 | imshow( corners_window, dst_norm_scaled ); 71 | } 72 | -------------------------------------------------------------------------------- /exercise5-harris-corner-detector/harris-corner-detector.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include "opencv2/core.hpp" 4 | #include "opencv2/viz.hpp" 5 | #include 6 | #include 7 | #include 8 | 9 | using namespace cv; 10 | using namespace std; 11 | /* 12 | * 13 | */ 14 | #define IMAGE1 "./image.png" 15 | #define IMAGE2 "./image2.png" 16 | #define SIGMA 3 17 | 18 | float gaus(int x, int y) { 19 | float sigma = SIGMA; 20 | float w = exp(-sqrt(x*x + y*y) / (2.0 * sigma * sigma)) / (2.0 * M_PI * sigma * sigma); 21 | ///cout << "x,y=" << x << ","<(0,0) += gaus(i-x,j-y)*(Ix.at(i,j)*Ix.at(i,j)) ; 32 | M.at(0,1) += gaus(i-x,j-y)*(Ix.at(i,j)*Iy.at(i,j)) ; 33 | M.at(1,1) += gaus(i-x,j-y)*(Iy.at(i,j)*Iy.at(i,j)) ; 34 | M.at(1,0) += gaus(i-x,j-y)*(Ix.at(i,j)*Iy.at(i,j)) ; 35 | } 36 | } 37 | //cout<< "M: " << M << endl; 38 | return M; 39 | } 40 | Mat getq(int x, int y, Mat Ix, Mat Iy, Mat dt) { 41 | 42 | Mat q = Mat::zeros(2,1, CV_32FC1); 43 | for(int i = x-SIGMA; i < x+SIGMA; i++) { 44 | for(int j = y-SIGMA; j < y+SIGMA; j++) { 45 | //cout << "dt: " << (int) dt.at(i,j) << endl; 46 | q.at(0,0) += gaus(i-x,j-y)*(Ix.at(i,j)*dt.at(i,j)) ; 47 | q.at(0,1) += gaus(i-x,j-y)*(Iy.at(i,j)*dt.at(i,j)) ; 48 | } 49 | } 50 | //cout<< "M: " << M << endl; 51 | return q; 52 | } 53 | 54 | string type2str(int type) { 55 | string r; 56 | 57 | uchar depth = type & CV_MAT_DEPTH_MASK; 58 | uchar chans = 1 + (type >> CV_CN_SHIFT); 59 | 60 | switch ( depth ) { 61 | case CV_8U: r = "8U"; break; 62 | case CV_8S: r = "8S"; break; 63 | case CV_16U: r = "16U"; break; 64 | case CV_16S: r = "16S"; break; 65 | case CV_32S: r = "32S"; break; 66 | case CV_32F: r = "32F"; break; 67 | case CV_64F: r = "64F"; break; 68 | default: r = "User"; break; 69 | } 70 | 71 | r += "C"; 72 | r += (chans+'0'); 73 | 74 | return r; 75 | } 76 | 77 | int main() 78 | { 79 | cout << "Built with OpenCV " << CV_VERSION << endl; 80 | 81 | Mat image = imread(IMAGE1); 82 | Mat image2 = imread(IMAGE2); 83 | 84 | cvtColor( image, image, CV_BGR2GRAY); 85 | cvtColor( image2, image2, CV_BGR2GRAY); 86 | 87 | string ty = type2str( image.type() ); 88 | printf("Matrix: %s %dx%d \n", ty.c_str(), image.cols, image.rows ); 89 | Mat Ix, Iy, Ixy; 90 | calculateGradient(image, Ix, Iy, Ixy); 91 | 92 | Mat Score = Mat(image.rows, image.cols, CV_8UC1); 93 | 94 | Mat dt = image - image2; 95 | for (int i = SIGMA; i < image.rows-SIGMA;i++) { 96 | for(int j = SIGMA; j < image.cols-SIGMA;j++) { 97 | Mat M = getM(i,j, Ix,Iy, Ixy); 98 | Score.at(i,j) = (char)( determinant(M)+0.05*(M.at(0,0)+M.at(1,1) )); 99 | if (Score.at(i,j) > 20 && Score.at(i,j) > Score.at(i-1,j-1) && 100 | Score.at(i,j) > Score.at(i-1,j) && 101 | Score.at(i,j) > Score.at(i-1,j+1) && 102 | Score.at(i,j) > Score.at(i,j+1) && 103 | Score.at(i,j) > Score.at(i+1,j+1) && 104 | Score.at(i,j) > Score.at(i+1,j) && 105 | Score.at(i,j) > Score.at(i+1,j-1) && 106 | Score.at(i,j) > Score.at(i,j-1) ) { 107 | //image.at(i,j) = 127; 108 | Mat q = getq(i, j, Ix, Iy, dt); 109 | //cout << "q: " << q << endl; 110 | Mat vel = M.inv()*q; 111 | //cout << vel << endl << endl; 112 | 113 | char vx =(char) vel.at(0,0); 114 | char vy =(char) vel.at(1,0); 115 | if ( vx*vx+vy*vy >= 1 ) { 116 | //cout <<(int) vx << ", " << (char) vy << endl; 117 | //image2.at(vy+i,vx+j) = 127; 118 | line(image, Point(j,i), Point(j,i), Scalar(255,255,255)); 119 | line(image2, Point(j+vx,i+vy), Point(j+vx,i+vy), Scalar(255,255,255)); 120 | 121 | //image2.at(i+vy,j+vx) = 27; 122 | 123 | } 124 | 125 | } 126 | 127 | } 128 | } 129 | // namedWindow("Sxy", WINDOW_AUTOSIZE ); 130 | // imshow( "Sxy", Score); 131 | namedWindow("Original image", WINDOW_AUTOSIZE ); 132 | imshow( "Original image", image); 133 | namedWindow("Original image 2", WINDOW_AUTOSIZE ); 134 | imshow( "Original image 2", image2); 135 | 136 | namedWindow("Dt", WINDOW_AUTOSIZE ); 137 | imshow( "Dt", dt); 138 | 139 | namedWindow("Gx", WINDOW_AUTOSIZE ); 140 | imshow( "Gx", Ix); 141 | namedWindow("Gy", WINDOW_AUTOSIZE ); 142 | imshow( "Gy", Iy); 143 | namedWindow("Gxy", WINDOW_AUTOSIZE ); 144 | imshow( "Gxy", Ixy); 145 | namedWindow("Sxy", WINDOW_AUTOSIZE ); 146 | imshow( "Sxy", Score); 147 | 148 | waitKey(0); 149 | 150 | return 0; 151 | } 152 | -------------------------------------------------------------------------------- /exercise6-eight-point-algorithm/AKAZE_match.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include 4 | #include 5 | #include 6 | #include "opencv2/viz.hpp" 7 | 8 | using namespace std; 9 | using namespace cv; 10 | 11 | const float inlier_threshold = 125.5f; // Distance threshold to identify inliers 12 | const float nn_match_ratio = 0.8f; // Nearest neighbor matching ratio 13 | //#define IMAGE1 "image.png" 14 | //#define IMAGE2 "image2.png" 15 | 16 | #define IMAGE1 "batinria0.tif" 17 | #define IMAGE2 "batinria1.tif" 18 | 19 | void drawPoints(Mat img, vector points, Mat& res) { 20 | res = img.clone(); 21 | for (int i=0;i< points.size();i++) { 22 | circle( res, 23 | points[i], 24 | 2.0, 25 | Scalar( 0, 0, 255 )); 26 | } 27 | } 28 | 29 | 30 | int main(void) 31 | { 32 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 33 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 34 | 35 | 36 | vector kpts1, kpts2; 37 | Mat desc1, desc2; 38 | 39 | Ptr akaze = AKAZE::create(); 40 | akaze->detectAndCompute(img1, noArray(), kpts1, desc1); 41 | akaze->detectAndCompute(img2, noArray(), kpts2, desc2); 42 | 43 | BFMatcher matcher(NORM_HAMMING); 44 | vector< vector > nn_matches; 45 | matcher.knnMatch(desc1, desc2, nn_matches, 2); 46 | 47 | vector points1, points2; //vectors to store the coordinates of the feature points 48 | vector matched1, matched2, inliers1, inliers2; 49 | vector good_matches; 50 | for(size_t i = 0; i < nn_matches.size(); i++) { 51 | DMatch first = nn_matches[i][0]; 52 | float dist1 = nn_matches[i][0].distance; 53 | float dist2 = nn_matches[i][1].distance; 54 | 55 | if(dist1 < nn_match_ratio * dist2) { 56 | matched1.push_back(kpts1[first.queryIdx]); 57 | matched2.push_back(kpts2[first.trainIdx]); 58 | } 59 | } 60 | 61 | for(unsigned i = 0; i < matched1.size(); i++) { 62 | Mat col = Mat::ones(3, 1, CV_64F); 63 | col.at(0) = matched1[i].pt.x; 64 | col.at(1) = matched1[i].pt.y; 65 | 66 | col /= col.at(2); 67 | double dist = sqrt( pow(col.at(0) - matched2[i].pt.x, 2) + 68 | pow(col.at(1) - matched2[i].pt.y, 2)); 69 | 70 | if(dist < inlier_threshold) { 71 | int new_i = static_cast(inliers1.size()); 72 | inliers1.push_back(matched1[i]); 73 | inliers2.push_back(matched2[i]); 74 | good_matches.push_back(DMatch(new_i, new_i, 0)); 75 | points1.push_back(matched1[i].pt); 76 | points2.push_back(matched2[i].pt); 77 | if (points1.size() == 10) break; 78 | } 79 | } 80 | 81 | Mat res; 82 | drawMatches(img1, inliers1, img2, inliers2, good_matches, res); 83 | imshow("res.png", res); 84 | //waitKey(0); 85 | double inlier_ratio = inliers1.size() * 1.0 / matched1.size(); 86 | cout << "A-KAZE Matching Results" << endl; 87 | cout << "*******************************" << endl; 88 | cout << "# Keypoints 1: \t" << kpts1.size() << endl; 89 | cout << "# Keypoints 2: \t" << kpts2.size() << endl; 90 | cout << "# Matches: \t" << matched1.size() << endl; 91 | cout << "# Inliers: \t" << inliers1.size() << endl; 92 | cout << "# Inliers Ratio: \t" << inlier_ratio << endl; 93 | cout << endl; 94 | /////////////////////// 95 | 96 | Mat res1, res2; 97 | drawPoints(img1, points1, res1); 98 | drawPoints(img2, points2, res2); 99 | imshow("matches1", res1); 100 | imshow("matches2", res2); 101 | //waitKey(0); 102 | //return 0; 103 | 104 | Mat E, R, t, mask; 105 | E = findEssentialMat(points2, points1);// focal, pp, RANSAC, 0.999, 1.0, mask); 106 | recoverPose(E, points2, points1, R, t);// focal, pp, mask); 107 | //cout << "E: " << E << endl; 108 | cout << "R: " << R << endl; 109 | cout << "t: " << t << endl; 110 | //cout << "x0: " << pointToMat(points2[0]) << endl; 111 | //printf("Matrix: %s %s \n", type2str(hat( pointToMat(points2[0])).type()).c_str(), type2str(t.type()).c_str()); 112 | 113 | //cout << "2 : " << hat( pointToMat(points2[0]))*t << endl; 114 | //cout << "1 : " << hat( pointToMat(points2[0]))*R*pointToMat(points1[0]) << endl; 115 | 116 | printType(R,"R type:"); 117 | printType(t,"t type:"); 118 | 119 | Mat M = Mat::zeros(3*points1.size(), points1.size()+1, CV_64F); 120 | assert(points1.size() == points2.size()); 121 | for (int i=0;i(3*i, i) = val1.at(0,0); 129 | M.at(3*i+1, i) = val1.at(1,0); 130 | M.at(3*i+2, i) = val1.at(2,0); 131 | 132 | M.at(3*i, points1.size()) = val2.at(0,0); 133 | M.at(3*i+1, points1.size()) = val2.at(1,0); 134 | M.at(3*i+2, points1.size()) = val2.at(2,0); 135 | } 136 | Mat Mt; 137 | transpose(M,Mt); 138 | Mat MM = Mt*M; 139 | cout<< "M:" << M << endl << endl; 140 | cout<< "Mt:" << Mt << endl << endl; 141 | cout<< "Mt*M:" << MM << endl << endl; 142 | 143 | Mat eigenVal, eigenVec; 144 | eigen(MM, eigenVal, eigenVec); 145 | cout << "Soluton:\n"; 146 | cout << "EigenVal: " << eigenVal << endl << endl; 147 | cout << "EigenVec: "<< eigenVec << endl << endl; 148 | Mat lambda = eigenVec.col(0); 149 | Mat gamma = eigenVec.col(points1.size() ); 150 | //return 0; 151 | //cout << points1.size(); 152 | 153 | cout << "Lambda: " << lambda << endl << endl; 154 | cout << "Gamma: " << gamma << endl << endl; 155 | printType(lambda, "lambda"); 156 | vector points_proj; 157 | for (int i=0; i< points1.size();i++) { 158 | points_proj.push_back(Point3f(points1[i].x, points2[i].y, ( (float) lambda.at(0,i) ) )); 159 | } 160 | 161 | 162 | viz::WCloud cloud_widget = viz::WCloud( points_proj, cv::viz::Color::green() ); 163 | cloud_widget.setRenderingProperty( cv::viz::POINT_SIZE, 2 ); 164 | viz::Viz3d trajectoryWindow("show"); 165 | 166 | trajectoryWindow.showWidget("point_cloud", cloud_widget); 167 | 168 | trajectoryWindow.spin(); 169 | waitKey(0); 170 | return 0; 171 | 172 | 173 | ///////////// 174 | return 0; 175 | } 176 | -------------------------------------------------------------------------------- /exercise6-eight-point-algorithm/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 22 | set(CMAKE_BUILD_TYPE Debug) 23 | 24 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 25 | # Add OpenCV headers location to your include paths 26 | include_directories(${OpenCV_INCLUDE_DIRS}) 27 | endif() 28 | 29 | # Declare the executable target built from your sources 30 | add_executable(opencv_example eight-point-algorithm-matlab-solution.cpp) 31 | 32 | # Link your application with OpenCV libraries 33 | target_link_libraries(opencv_example ${OpenCV_LIBS}) 34 | -------------------------------------------------------------------------------- /exercise6-eight-point-algorithm/eight-point-algorithm-matlab-solution.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | #include 6 | #include 7 | #include "opencv2/viz.hpp" 8 | #include "../common.h" 9 | 10 | using namespace std; 11 | using namespace cv; 12 | 13 | //#define IMAGE1 "image.png" 14 | //#define IMAGE2 "image2.png" 15 | 16 | #define IMAGE1 "batinria0.tif" 17 | #define IMAGE2 "batinria1.tif" 18 | 19 | 20 | //% Compute correct combination of R and T and reconstruction of 3D points 21 | void reconstruction(Mat R, Mat T, vector points1, vector points2) { 22 | 23 | int nPoints = points1.size(); 24 | Mat M = Mat::zeros(3*nPoints, nPoints+1, CV_32F ); 25 | for (int i = 0; i(3*i, i) = val1.at(0,0); 32 | M.at(3*i+1, i) = val1.at(1,0); 33 | M.at(3*i+2, i) = val1.at(2,0); 34 | 35 | M.at(3*i, nPoints) = val2.at(0,0); 36 | M.at(3*i+1, nPoints) = val2.at(1,0); 37 | M.at(3*i+2, nPoints) = val2.at(2,0); 38 | } 39 | 40 | //% Get depth values (eigenvector to the smallest eigenvalue of M'M): 41 | Mat Mt; 42 | transpose(M,Mt); 43 | Mat MM = Mt*M; 44 | 45 | Mat eigenVal, eigenVec; 46 | 47 | eigen(MM, eigenVal, eigenVec); 48 | Mat lambda = eigenVec.row(eigenVec.rows-1); 49 | float gamma = eigenVec.at(nPoints,nPoints); 50 | 51 | cout << "Lambda: " << lambda << endl; 52 | cout << "Gamma: " << gamma << endl; 53 | vector points_proj; 54 | for (int i=0; i< points1.size();i++) { 55 | points_proj.push_back(Point3f(points1[i].x, points1[i].y, lambda.at(0,i) )); 56 | } 57 | 58 | 59 | viz::WCloud cloud_widget = viz::WCloud( points_proj, cv::viz::Color::green() ); 60 | cloud_widget.setRenderingProperty( cv::viz::POINT_SIZE, 2 ); 61 | viz::Viz3d trajectoryWindow("show"); 62 | 63 | trajectoryWindow.showWidget("point_cloud", cloud_widget); 64 | 65 | trajectoryWindow.spin(); 66 | 67 | } 68 | 69 | 70 | 71 | void getPredefinedPoints(vector &v1, vector &v2) { 72 | float x1[] = {10, 92, 8, 92, 289, 354, 289, 353, 73 | 69, 294, 44, 336}; 74 | 75 | float y1[] = {232, 230, 334, 333, 230, 278, 76 | 340, 332, 90, 149, 475, 433}; 77 | 78 | float x2[] = {123, 203, 123, 202, 397, 472, 398, 472, 79 | 182, 401, 148, 447}; 80 | 81 | float y2[] = {239, 237, 338, 338, 236, 286, 82 | 348, 341, 99, 153, 471, 445}; 83 | 84 | for (int i=0;i<12;i++) { 85 | v1.push_back(Point2f(x1[i],y1[i])); 86 | v2.push_back(Point2f(x2[i],y2[i])); 87 | } 88 | } 89 | const float inlier_threshold = 125.5f; // Distance threshold to identify inliers 90 | const float nn_match_ratio = 0.8f; // Nearest neighbor matching ratio 91 | 92 | int main() { 93 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 94 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 95 | vector points1, points2; 96 | getPredefinedPoints(points1, points2); 97 | /*vector kpts1, kpts2; 98 | Mat desc1, desc2; 99 | 100 | Ptr akaze = AKAZE::create(); 101 | akaze->detectAndCompute(img1, noArray(), kpts1, desc1); 102 | akaze->detectAndCompute(img2, noArray(), kpts2, desc2); 103 | 104 | BFMatcher matcher(NORM_HAMMING); 105 | vector< vector > nn_matches; 106 | matcher.knnMatch(desc1, desc2, nn_matches, 2); 107 | 108 | vector matched1, matched2, inliers1, inliers2; 109 | vector good_matches; 110 | for(size_t i = 0; i < nn_matches.size(); i++) { 111 | DMatch first = nn_matches[i][0]; 112 | float dist1 = nn_matches[i][0].distance; 113 | float dist2 = nn_matches[i][1].distance; 114 | 115 | if(dist1 < nn_match_ratio * dist2) { 116 | matched1.push_back(kpts1[first.queryIdx]); 117 | matched2.push_back(kpts2[first.trainIdx]); 118 | } 119 | } 120 | 121 | for(unsigned i = 0; i < matched1.size(); i++) { 122 | Mat col = Mat::ones(3, 1, CV_64F); 123 | col.at(0) = matched1[i].pt.x; 124 | col.at(1) = matched1[i].pt.y; 125 | 126 | col /= col.at(2); 127 | double dist = sqrt( pow(col.at(0) - matched2[i].pt.x, 2) + 128 | pow(col.at(1) - matched2[i].pt.y, 2)); 129 | 130 | if(dist < inlier_threshold) { 131 | int new_i = static_cast(inliers1.size()); 132 | inliers1.push_back(matched1[i]); 133 | inliers2.push_back(matched2[i]); 134 | good_matches.push_back(DMatch(new_i, new_i, 0)); 135 | points1.push_back(matched1[i].pt); 136 | points2.push_back(matched2[i].pt); 137 | if (points1.size() == 1000) break; 138 | } 139 | } 140 | Mat res; 141 | drawMatches(img1, inliers1, img2, inliers2, good_matches, res); 142 | imshow("res.png", res); 143 | //waitKey(0); 144 | double inlier_ratio = inliers1.size() * 1.0 / matched1.size(); 145 | cout << "A-KAZE Matching Results" << endl; 146 | cout << "*******************************" << endl; 147 | cout << "# Keypoints 1: \t" << kpts1.size() << endl; 148 | cout << "# Keypoints 2: \t" << kpts2.size() << endl; 149 | cout << "# Matches: \t" << matched1.size() << endl; 150 | cout << "# Inliers: \t" << inliers1.size() << endl; 151 | cout << "# Inliers Ratio: \t" << inlier_ratio << endl; 152 | cout << endl; 153 | */ 154 | ////////////// 155 | float k1[] = {844.310547, 0, 243.413315, 0, 1202.508301, 281.529236, 0, 0, 1}; 156 | float k2[] = {852.721008, 0, 252.021805, 0, 1215.657349, 288.587189, 0, 0, 1}; 157 | Mat K1 = Mat(3,3, CV_32F, k1); 158 | Mat K2 = Mat(3,3, CV_32F, k2); 159 | K1 = K1.inv(); 160 | K2 = K2.inv(); 161 | //printVector(points1); 162 | for (int i=0;i < points1.size();i++ ){ 163 | Mat rp; 164 | //cout << "before P: " << points1[i] << endl; 165 | rp = K1*pointToMat(points1[i]); 166 | //cout << pointToMat(points1[i]) << endl; 167 | points1[i].x = rp.at(0,0); 168 | points1[i].y = rp.at(0,1); 169 | //cout << "after P: " << points1[i] << endl; 170 | 171 | rp = K2*pointToMat(points2[i]); 172 | points2[i].x = rp.at(0,0); 173 | points2[i].y = rp.at(0,1); 174 | } 175 | //printVector(points1); 176 | Mat chi = Mat::zeros(points1.size(),9, CV_32F); 177 | vector krons; 178 | for (int i = 0;i Ev; 192 | v.col(8).copyTo(Ev); 193 | 194 | //cout<< "Ev: "; printVector(Ev); 195 | //cout << "Es: " << << endl; 196 | Mat E = Mat(3,3, CV_32F, &Ev[0]); 197 | transpose(E,E); 198 | //cout << "E: "; printMat(E); 199 | 200 | SVD Esvd = SVD(E); 201 | Mat EsvdV; 202 | transpose( Esvd.vt, EsvdV); 203 | 204 | //cout << "Esvd.u: "; printMat(Esvd.u); 205 | //cout << "Esvd.v: "; printMat(EsvdV); 206 | 207 | if (determinant(Esvd.u) < 0 || determinant(EsvdV) < 0) { 208 | Esvd = SVD(-E); 209 | //cout << "changed sing\n"; 210 | } 211 | 212 | Mat D = Mat::zeros(3,3, CV_32F); 213 | D.at(0,0) = 1; 214 | D.at(1,1) = 1; 215 | D.at(2,2) = 0; 216 | 217 | E = Esvd.u*D*Esvd.vt; 218 | Mat U = Esvd.u; 219 | Mat Vr = transpose(Esvd.u); 220 | 221 | Mat Vt = Esvd.vt; 222 | //cout << "project E: "; 223 | //printMat(E); 224 | //cout << "OpenCV E:"; 225 | //printMat( findEssentialMat(points1, points2)); 226 | 227 | 228 | float rz1[] = {0, -1, 0, 1, 0, 0, 0, 0, 1}; 229 | float rz2[] = {0, 1, 0, -1, 0, 0, 0, 0, 1}; 230 | Mat Rz1 = Mat(3,3,CV_32F, rz1); 231 | Mat Rz2 = Mat(3,3,CV_32F, rz2); 232 | 233 | Mat R1 = U * transpose( Rz1) * Vt; 234 | Mat R2 = U * transpose( Rz2) * Vt; 235 | Mat Ut = transpose(U); 236 | Mat T_hat1 = U * Rz1 * D * Ut; 237 | Mat T_hat2 = U * Rz2 * D * Ut; 238 | 239 | cout << "R1: "; printMat(R1); 240 | //cout << "R2: "; printMat(R2); 241 | 242 | //% Translation belonging to T_hat 243 | Mat T1 = Mat::zeros(3,1, CV_32F); 244 | Mat T2 = Mat::zeros(3,1, CV_32F); 245 | 246 | T1.at(0,0) = -T_hat1.at(1,2); 247 | T1.at(1,0) = T_hat1.at(0,2); 248 | T1.at(2,0) = -T_hat1.at(0,1); 249 | 250 | T2.at(0,0) = -T_hat2.at(1,2); 251 | T2.at(1,0) = T_hat2.at(0,2); 252 | T2.at(2,0) = -T_hat2.at(0,1); 253 | 254 | cout << "T1: "; 255 | printMat(T1); 256 | //cout << "T2: "; 257 | //printMat(T2); 258 | 259 | reconstruction(R1, T1, points1, points2); 260 | reconstruction(R1, T2, points1, points2); 261 | reconstruction(R2, T1, points1, points2); 262 | reconstruction(R2, T2, points1, points2); 263 | 264 | return 0; 265 | } 266 | 267 | /* 268 | 269 | 270 | % Compute scene reconstruction and correct combination of R and T: 271 | reconstruction(R1,T1,x1,y1,x2,y2,nPoints); 272 | reconstruction(R1,T2,x1,y1,x2,y2,nPoints); 273 | reconstruction(R2,T1,x1,y1,x2,y2,nPoints); 274 | reconstruction(R2,T2,x1,y1,x2,y2,nPoints); 275 | 276 | end 277 | 278 | 279 | 280 | 281 | 282 | 283 | 284 | 285 | % ================ 286 | % Hat-function 287 | function A = hat(v) 288 | A = [0 -v(3) v(2) ; v(3) 0 -v(1) ; -v(2) v(1) 0]; 289 | end 290 | 291 | 292 | 293 | % ================ 294 | % function getpoints 295 | function [x1,y1,x2,y2] = getpoints(image1,image2,nPoints) 296 | 297 | x1 = zeros(nPoints,1); 298 | y1 = zeros(nPoints,1); 299 | x2 = zeros(nPoints,1); 300 | y2 = zeros(nPoints,1); 301 | 302 | % Click points in image1: 303 | % Can be done without for-loop: ginput(nPoints) 304 | figure; imshow(uint8(image1)); 305 | hold on; 306 | for i = 1:nPoints 307 | [x,y] = ginput(1); 308 | x1(i) = double(x); 309 | y1(i) = double(y); 310 | plot(x, y, 'r+'); 311 | end 312 | hold off; 313 | 314 | 315 | % Click points in image2: 316 | figure; imshow(uint8(image2)); 317 | hold on; 318 | for i = 1:nPoints 319 | [x,y] = ginput(1); 320 | x2(i) = double(x); 321 | y2(i) = double(y); 322 | plot(x, y, 'r+'); 323 | end 324 | hold off; 325 | 326 | end 327 | 328 | 329 | 330 | % ================ 331 | % function getpoints2 --> points already defined 332 | function [x1,y1,x2,y2] = getpoints2() 333 | 334 | x1 = [ 335 | 10 336 | 92 337 | 8 338 | 92 339 | 289 340 | 354 341 | 289 342 | 353 343 | 69 344 | 294 345 | 44 346 | 336 347 | ]; 348 | 349 | y1 = [ 350 | 232 351 | 230 352 | 334 353 | 333 354 | 230 355 | 278 356 | 340 357 | 332 358 | 90 359 | 149 360 | 475 361 | 433 362 | ]; 363 | 364 | x2 = [ 365 | 123 366 | 203 367 | 123 368 | 202 369 | 397 370 | 472 371 | 398 372 | 472 373 | 182 374 | 401 375 | 148 376 | 447 377 | ]; 378 | 379 | y2 = [ 380 | 239 381 | 237 382 | 338 383 | 338 384 | 236 385 | 286 386 | 348 387 | 341 388 | 99 389 | 153 390 | 471 391 | 445 392 | ]; 393 | 394 | end 395 | */ 396 | -------------------------------------------------------------------------------- /exercise6-eight-point-algorithm/eight-point-algorithm.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | #include 6 | #include 7 | #include "opencv2/viz.hpp" 8 | 9 | using namespace std; 10 | using namespace cv; 11 | 12 | const float inlier_threshold = 152.5f; // Distance threshold to identify inliers 13 | const float nn_match_ratio = 0.8f; // Nearest neighbor matching ratio 14 | 15 | 16 | #define IMAGE1 "image.png" 17 | #define IMAGE2 "image2.png" 18 | 19 | //#define IMAGE1 "batinria0.tif" 20 | //#define IMAGE2 "batinria1.tif" 21 | 22 | 23 | void featureTracking(Mat img_1, Mat img_2, vector& points1, vector& points2, vector& status) { 24 | 25 | //this function automatically gets rid of points for which tracking fails 26 | 27 | vector err; 28 | Size winSize=Size(15,15); 29 | TermCriteria termcrit=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01); 30 | 31 | calcOpticalFlowPyrLK(img_1, img_2, points1, points2, status, err, winSize, 3, termcrit, 0, 0.001); 32 | 33 | 34 | //getting rid of points for which the KLT tracking failed or those who have gone outside the frame 35 | int indexCorrection = 0; 36 | for( int i=0; i& points1, vector &keypoints_1) { //uses FAST as of now, modify parameters as necessary 50 | //vector keypoints_1; 51 | int fast_threshold = 20; 52 | bool nonmaxSuppression = true; 53 | FAST(img_1, keypoints_1, fast_threshold, nonmaxSuppression); 54 | KeyPoint::convert(keypoints_1, points1, vector()); 55 | 56 | } 57 | 58 | 59 | 60 | int main(void) { 61 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 62 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 63 | 64 | vector keypoints_1, keypoints_2; 65 | 66 | vector points1, points2; //vectors to store the coordinates of the feature points 67 | featureDetection(img1, points1, keypoints_1); //detect features in img_1 68 | featureDetection(img2, points2, keypoints_2); //detect features in img_1 69 | 70 | vector status; 71 | featureTracking(img1,img2,points1,points2, status); //track those features to img_2 72 | 73 | Mat res1, res2; 74 | drawPoints(img1, points1, res1); 75 | drawPoints(img2, points2, res2); 76 | imshow("matches1", res1); 77 | imshow("matches2", res2); 78 | //waitKey(0); 79 | //return 0; 80 | Mat E, R, t, mask; 81 | E = findEssentialMat(points2, points1);// focal, pp, RANSAC, 0.999, 1.0, mask); 82 | recoverPose(E, points2, points1, R, t);// focal, pp, mask); 83 | //cout << "E: " << E << endl; 84 | cout << "R: " << R << endl; 85 | cout << "t: " << t << endl; 86 | //cout << "x0: " << pointToMat(points2[0]) << endl; 87 | //printf("Matrix: %s %s \n", type2str(hat( pointToMat(points2[0])).type()).c_str(), type2str(t.type()).c_str()); 88 | 89 | //cout << "2 : " << hat( pointToMat(points2[0]))*t << endl; 90 | //cout << "1 : " << hat( pointToMat(points2[0]))*R*pointToMat(points1[0]) << endl; 91 | 92 | Mat M = Mat::zeros(3*points1.size(), points1.size()+1, CV_64F); 93 | assert(points1.size() == points2.size()); 94 | for (int i=0;i(3*i, i) = val1.at(0,0); 102 | M.at(3*i+1, i) = val1.at(1,0); 103 | M.at(3*i+2, i) = val1.at(2,0); 104 | 105 | M.at(3*i, points1.size()) = val2.at(0,0); 106 | M.at(3*i+1, points1.size()) = val2.at(1,0); 107 | M.at(3*i+2, points1.size()) = val2.at(2,0); 108 | } 109 | Mat Mt; 110 | transpose(M,Mt); 111 | Mat MM = Mt*M; 112 | cout<< "M:" << M << endl; 113 | cout<< "Mt:" << Mt << endl; 114 | cout<< "Mt*M:" << MM << endl; 115 | 116 | Mat eigenVal, eigenVec; 117 | eigen(MM, eigenVal, eigenVec); 118 | cout << "Soluton:\n"; 119 | //cout << "EigenVal: " << eigenVal << endl; 120 | //cout << "EigenVec: " << eigenVec << endl; 121 | Mat lambda = eigenVec.col(0); 122 | Mat gamma = eigenVec.col(points1.size() ); 123 | //return 0; 124 | //cout << points1.size(); 125 | 126 | cout << "Lambda: " << lambda << endl; 127 | //cout << "Gamma: " << gamma << endl; 128 | printType(lambda, "lambda"); 129 | vector points_proj; 130 | for (int i=0; i< points1.size();i++) { 131 | points_proj.push_back(Point3f(points1[i].x, points2[i].y, ( (float) lambda.at(0,i) )*100 )); 132 | } 133 | 134 | 135 | viz::WCloud cloud_widget = viz::WCloud( points_proj, cv::viz::Color::green() ); 136 | cloud_widget.setRenderingProperty( cv::viz::POINT_SIZE, 2 ); 137 | viz::Viz3d trajectoryWindow("show"); 138 | 139 | trajectoryWindow.showWidget("point_cloud", cloud_widget); 140 | 141 | trajectoryWindow.spin(); 142 | waitKey(0); 143 | return 0; 144 | } 145 | 146 | -------------------------------------------------------------------------------- /exercise7-direct-methods-1/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_mvg_exercise_direct_methods) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 22 | set(CMAKE_BUILD_TYPE Debug) 23 | 24 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 25 | # Add OpenCV headers location to your include paths 26 | include_directories(${OpenCV_INCLUDE_DIRS}) 27 | endif() 28 | 29 | # Declare the executable target built from your sources 30 | add_executable(direct-methods direct-methods.cpp) 31 | 32 | # Link your application with OpenCV libraries 33 | target_link_libraries(direct-methods ${OpenCV_LIBS}) 34 | -------------------------------------------------------------------------------- /exercise7-direct-methods-1/depth/1305031102.160407.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/depth/1305031102.160407.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/depth/1305031102.262886.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/depth/1305031102.262886.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/depth/1341847980.723020.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/depth/1341847980.723020.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/depth/1341847982.998830.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/depth/1341847982.998830.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/direct-methods.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | #include 6 | #include 7 | #include // std::numeric_limits 8 | #include 9 | #include "../common.h" 10 | 11 | using namespace std; 12 | using namespace cv; 13 | 14 | 15 | /*#define IMAGE1 "/home/smith/Work/sdvo-phone/test-footy/rgb/1341847980.722988.png" 16 | #define IMAGE2 "/home/smith/Work/sdvo-phone/test-footy/rgb/1341847982.998783.png" 17 | #define IMAGE1_DEPTH "/home/smith/Work/sdvo-phone/test-footy/depth/1341847980.723020.png" 18 | #define IMAGE2_DEPTH "/home/smith/Work/sdvo-phone/test-footy/depth/1341847982.998830.png" 19 | #define k_values { 535.4, 0, 320.1, 0, 539.2, 247.6, 0, 0, 1} 20 | */ 21 | 22 | #define IMAGE1 "../rgb/1305031102.175304.png" 23 | #define IMAGE2 "../rgb/1305031102.275326.png" 24 | #define IMAGE1_DEPTH "../depth/1305031102.160407.png" 25 | #define IMAGE2_DEPTH "../depth/1305031102.262886.png" 26 | #define k_values { 517.3, 0, 318.6, 0, 516.5, 255.3, 0, 0, 1} 27 | 28 | 29 | 30 | #define LVL 5 31 | 32 | float dNaN = numeric_limits::quiet_NaN(); 33 | void deriveErrAnalitic(Mat_ IRef, Mat_ DRef, Mat_ I, Mat_ xi, Mat_ K, Mat_& Jac, Mat& residual, int lvl ) { 34 | Mat T = se3Exp(xi); 35 | Mat R = T(cv::Rect(0,0,3,3)); 36 | Mat t = T(cv::Rect(3,0,1,3)); 37 | 38 | Mat RKInv = R * K.inv(); 39 | 40 | Mat_ Img = Mat(IRef.rows, IRef.cols,CV_32F, dNaN); 41 | Mat_ dyI, dxI; 42 | calculateGradients(I, dxI, dyI); 43 | Mat_ dxImg = Mat(IRef.rows, IRef.cols, CV_32F, dNaN); 44 | Mat_ dyImg = Mat(IRef.rows, IRef.cols, CV_32F, dNaN); 45 | 46 | Mat_ xImg = Mat(IRef.rows, IRef.cols,CV_32F, dNaN); 47 | Mat_ yImg = Mat(IRef.rows, IRef.cols,CV_32F, dNaN); 48 | 49 | Mat_ xp = Mat(IRef.rows, IRef.cols, CV_32F, dNaN); 50 | Mat_ yp = Mat(IRef.rows, IRef.cols, CV_32F, dNaN); 51 | Mat_ zp = Mat(IRef.rows, IRef.cols, CV_32F, dNaN); 52 | 53 | for (int x=0; x< IRef.rows; x++) { 54 | for (int y=0; y< IRef.cols; y++) { 55 | if (DRef.at(x,y) > 0) { 56 | 57 | Mat_ p = Mat( Point3d(x,y,1)) * DRef(x,y); 58 | Mat_ pTrans = ( RKInv * p + t ); 59 | if (pTrans(2, 0) > 0 ) { 60 | Mat_ pTransProj = K*pTrans; 61 | 62 | xImg(x,y) = pTransProj(0,0)/pTransProj(2,0); 63 | yImg(x,y) = pTransProj(1,0)/pTransProj(2,0); 64 | 65 | xp(x, y) = pTrans(0,0); 66 | yp(x, y) = pTrans(1,0); 67 | zp(x, y) = pTrans(2,0); 68 | } 69 | } 70 | } 71 | } 72 | 73 | remap(I, Img, yImg, xImg, CV_INTER_LINEAR, BORDER_CONSTANT, dNaN); 74 | 75 | remap(dxI, dxImg, yImg, xImg, CV_INTER_LINEAR, BORDER_CONSTANT, dNaN); 76 | remap(dyI, dyImg, yImg, xImg, CV_INTER_LINEAR, BORDER_CONSTANT, dNaN); 77 | 78 | dxImg = K(0,0) * dxImg.reshape(1, dxImg.rows*dxImg.cols); 79 | dyImg = K(1,1) * dyImg.reshape(1, dyImg.rows*dyImg.cols); 80 | 81 | xp = xp.reshape(1, xp.rows*xp.cols); 82 | yp = yp.reshape(1, yp.rows*yp.cols); 83 | zp = zp.reshape(1, zp.rows*zp.cols); 84 | 85 | Jac = Mat::zeros(Img.cols * Img.rows, 6, CV_32F); 86 | 87 | for (int i=0;i errU8; 101 | err.convertTo(errU8, CV_8U); 102 | upscaleImage(errU8, lvl); 103 | for (int row = 0; row 250 ) { 106 | errU8(row,col) = 0; 107 | } 108 | } 109 | } 110 | imshow("err", errU8); 111 | waitKey(0); 112 | residual = err.reshape(1, err.rows*err.cols); 113 | } 114 | 115 | int main() { 116 | int lvl = LVL; 117 | 118 | float k[] = k_values; 119 | Mat_ K = Mat(3,3, CV_32F, k); 120 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 121 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 122 | 123 | imshow("start ", img1-img2); 124 | imshow("img1: ", img1); 125 | imshow("img2: ", img2); 126 | 127 | Mat img1_depth = imread(IMAGE1_DEPTH, IMREAD_ANYDEPTH); 128 | Mat img2_depth = imread(IMAGE2_DEPTH, IMREAD_ANYDEPTH); 129 | 130 | img1.convertTo(img1, CV_32F); 131 | img1_depth.convertTo(img1_depth, CV_32F); 132 | img2.convertTo(img2, CV_32F); 133 | img2_depth.convertTo(img2_depth, CV_32F); 134 | Mat xi = Mat::zeros(1,6,CV_32F); 135 | //float xi_solution[] = xi_values; 136 | //Mat xi = Mat(1,6,CV_32F, xi_solution); 137 | 138 | Mat IRef = img1.clone(); 139 | Mat ITwo = img2.clone(); 140 | Mat DRef = img1_depth.clone(); 141 | Mat_ Klvl = K.clone(); 142 | 143 | for (;lvl>1;lvl--) { 144 | Mat IRef = img1.clone(); 145 | Mat ITwo = img2.clone(); 146 | Mat DRef = img1_depth.clone(); 147 | Mat_ Klvl = K.clone(); 148 | 149 | downscaleImage(IRef, lvl); 150 | downscaleDepth(DRef, lvl); 151 | downscaleImage(ITwo, lvl); 152 | downscaleK(Klvl, lvl); 153 | cout << lvl << endl; 154 | 155 | Mat_ Jac; 156 | Mat_ residual; 157 | 158 | Scalar errScalar; 159 | float err; 160 | float errLast = 99999; 161 | for (int i=0; i<10; i++) { 162 | 163 | deriveErrAnalitic(IRef, DRef, ITwo, xi, Klvl, Jac, residual, lvl); 164 | 165 | for (int row = 0; row < Jac.rows; row++) { 166 | for(int col = 0; col < Jac.cols; col++) { 167 | if ( isnan(Jac(row,col)) || isnan(residual(row,0) || abs( Jac(row,col)) > 10000 )) { 168 | for(int col2 = 0; col2 < Jac.cols; col2++) { 169 | Jac(row, col2) = (float)0; 170 | } 171 | residual(row,0) = 0; 172 | } 173 | } 174 | } 175 | 176 | Mat upd = - ( transpose(Jac) * Jac).inv(DECOMP_SVD)* (transpose(Jac)* residual); 177 | xi = se3Log(se3Exp(upd) * se3Exp(xi)); 178 | cout <<"updated Xi: "; printMat(xi); 179 | float sumErr = 0; 180 | Mat_ resid2 = residual.clone(); 181 | for (int item=0; item 0.99) { 190 | break; 191 | } 192 | errLast = err; 193 | } 194 | } 195 | waitKey(0); 196 | 197 | return 0; 198 | } 199 | 200 | -------------------------------------------------------------------------------- /exercise7-direct-methods-1/rgb/1305031102.175304.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/rgb/1305031102.175304.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/rgb/1305031102.275326.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/rgb/1305031102.275326.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/rgb/1341847980.722988.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/rgb/1341847980.722988.png -------------------------------------------------------------------------------- /exercise7-direct-methods-1/rgb/1341847982.998783.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise7-direct-methods-1/rgb/1341847982.998783.png -------------------------------------------------------------------------------- /exercise8-epipolarLines/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 22 | set(CMAKE_BUILD_TYPE Debug) 23 | 24 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 25 | # Add OpenCV headers location to your include paths 26 | include_directories(${OpenCV_INCLUDE_DIRS}) 27 | endif() 28 | 29 | # Declare the executable target built from your sources 30 | add_executable(opencv_example epipolar-line.cpp) 31 | 32 | # Link your application with OpenCV libraries 33 | target_link_libraries(opencv_example ${OpenCV_LIBS}) 34 | -------------------------------------------------------------------------------- /exercise8-epipolarLines/epipolar-line.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | #include 6 | #include 7 | #include "opencv2/viz.hpp" 8 | #include // std::numeric_limits 9 | #include 10 | #include "../common.h" 11 | 12 | using namespace std; 13 | using namespace cv; 14 | #define k_values { 535.4, 0, 320.1, 0, 539.2, 247.6, 0, 0, 1} 15 | 16 | #define IMAGE1 "./batinria0.pgm" 17 | #define IMAGE2 "./batinria1.pgm" 18 | 19 | typedef float MatType; 20 | 21 | 22 | int main() { 23 | 24 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 25 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 26 | 27 | //% Left camera parameters: 28 | MatType k1[] = {844.310547, 0, 243.413315, 0, 1202.508301, 281.529236, 0, 0, 1}; 29 | 30 | MatType g1_values[] = {0.655133, 0.031153, 0.754871, -793.848328, 31 | 0.003613, 0.999009, -0.044364, 269.264465, 32 | -0.755505, 0.031792, 0.654371, -744.572876, 33 | 0 , 0 , 0 , 1}; 34 | 35 | 36 | //% Right camera parameters: 37 | MatType k2[] = {852.721008, 0, 252.021805, 0, 1215.657349, 288.587189, 0, 0, 1}; 38 | MatType g2_values[] = {0.739514, 0.034059, 0.672279, -631.052917, 39 | -0.006453, 0.999032, -0.043515, 270.192749, 40 | -0.673111, 0.027841, 0.739017, -935.050842, 41 | 0 , 0 , 0 , 1}; 42 | 43 | //% Compute the fundamental matrix: 44 | Mat_ g1 = Mat_(4,4, g1_values); 45 | Mat_ g2 = Mat_(4,4, g2_values); 46 | Mat_ K1 = Mat_(3,3, k1); 47 | Mat_ K2 = Mat_(3,3, k2); 48 | 49 | 50 | Mat_ g = (g2.inv()) * (g1); 51 | 52 | Mat t = g(Rect(3,0,1,3)); 53 | Mat R = g(Rect(0,0,3,3)); 54 | 55 | //cout << "g: "; printMat(g); 56 | 57 | //cout << "T: "; printMat(T); 58 | //cout << "hat T: "; printMat(hat(T)); 59 | //cout << "R: "; printMat(R); 60 | //cout << "transpose(K2.inv()): "; printMat(transpose(K2.inv())); 61 | //cout << "hat(T): "; printMat(hat(T)); 62 | //cout << "R: "; printMat(R); 63 | //cout << "K1.inv(): "; printMat( K1.inv()); 64 | 65 | cout << "K2.inv: "; printMat(K2.inv()); 66 | 67 | Mat_ F = transpose(K2.inv()) * hat(t) * R * K1.inv(); 68 | cout << "F: "; printMat(F); 69 | 70 | int x, y; 71 | x = 68; 72 | y = 90; 73 | 74 | //plot(x1,y1,'r+'); 75 | //hold off; 76 | 77 | //% Compute epipolar line for x1: 78 | Mat_ point = Mat_(3,1); 79 | point(0,0) = x; 80 | point(0,1) = y; 81 | point(0,2) = 1; 82 | 83 | printMat(point); 84 | Mat_ l = F * point; 85 | 86 | //printMat(F); 87 | cout<< "l: ";printMat(l); 88 | int w = img2.cols; 89 | //% Draw epipolar line in image2: 90 | //figure; imshow(uint8(image2)); 91 | //hold on; 92 | MatType m = -l(0,0)/l(1,0); 93 | MatType b = -l(2,0)/l(1,0); 94 | cout << "m: " << m << " b: " << b << endl; 95 | 96 | int y1 = (int) round( m * 1 + b); 97 | int y2 = (int) round(m * w + b); 98 | 99 | //line([1 w],[y1 y2]) 100 | line(img2, Point(1,y1), Point(w,y2), Scalar(255,255,255)); 101 | circle(img1, Point(x,y), 4, Scalar(255,255,255)); 102 | 103 | cout << w <<", "<< y1 << ", " << y2 << endl; 104 | 105 | imshow("image1", img1); 106 | imshow("image2", img2); 107 | waitKey(0); 108 | return 0; 109 | } 110 | 111 | -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | # cmake needs this line 2 | cmake_minimum_required(VERSION 2.8) 3 | 4 | # Define project name 5 | project(opencv_example_project) 6 | 7 | # Find OpenCV, you may need to set OpenCV_DIR variable 8 | # to the absolute path to the directory containing OpenCVConfig.cmake file 9 | # via the command line or GUI 10 | find_package(OpenCV REQUIRED) 11 | 12 | # If the package has been found, several variables will 13 | # be set, you can find the full list with descriptions 14 | # in the OpenCVConfig.cmake file. 15 | # Print some message showing some of them 16 | message(STATUS "OpenCV library status:") 17 | message(STATUS " version: ${OpenCV_VERSION}") 18 | message(STATUS " libraries: ${OpenCV_LIBS}") 19 | message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}") 20 | 21 | set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ") 22 | set(CMAKE_BUILD_TYPE Debug) 23 | 24 | if(CMAKE_VERSION VERSION_LESS "2.8.11") 25 | # Add OpenCV headers location to your include paths 26 | include_directories(${OpenCV_INCLUDE_DIRS}) 27 | endif() 28 | 29 | # Declare the executable target built from your sources 30 | add_executable(direct-methods direct-methods.cpp) 31 | 32 | 33 | # Link your application with OpenCV libraries 34 | target_link_libraries(direct-methods ${OpenCV_LIBS}) 35 | 36 | #target_link_libraries(opticalFlow ${OpenCV_LIBS}) 37 | -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/depth/1305031102.160407.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/depth/1305031102.160407.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/depth/1305031102.262886.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/depth/1305031102.262886.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/depth/1341847980.723020.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/depth/1341847980.723020.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/depth/1341847982.998830.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/depth/1341847982.998830.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/direct-methods.cpp: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | #include 6 | #include 7 | //#include "opencv2/viz.hpp" 8 | #include // std::numeric_limits 9 | #include 10 | #include "../common.h" 11 | 12 | using namespace std; 13 | using namespace cv; 14 | /* 15 | #define IMAGE1 "./rgb/1341847980.722988.png" 16 | #define IMAGE2 "./rgb/1341847982.998783.png" 17 | #define IMAGE1_DEPTH "./depth/1341847980.723020.png" 18 | #define IMAGE2_DEPTH "./depth/1341847982.998830.png" 19 | #define k_values { 535.4, 0, 320.1, 0, 539.2, 247.6, 0, 0, 1} 20 | */ 21 | #define IMAGE1 "../rgb/1305031102.175304.png" 22 | #define IMAGE2 "../rgb/1305031102.275326.png" 23 | #define IMAGE1_DEPTH "../depth/1305031102.160407.png" 24 | #define IMAGE2_DEPTH "../depth/1305031102.262886.png" 25 | #define k_values { 535.4, 0, 320.1, 0, 539.2, 247.6, 0, 0, 1} 26 | 27 | #define LVL 5 28 | Mat calcErr(Mat_ IRef_, Mat_ DRef, Mat_ I, Mat_ xi, Mat_ K, int lvl ) { 29 | Mat_ IRef = IRef_.clone(); 30 | Mat T = se3Exp(xi); 31 | Mat R = T(cv::Rect(0,0,3,3)); 32 | Mat t = T(cv::Rect(3,0,1,3)); 33 | Mat RKInv = R * K.inv(); 34 | 35 | //float dNaN = numeric_limits::quiet_NaN(); 36 | Mat_ Img = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 37 | 38 | for (int x=0; x< IRef.rows; x++) { 39 | for (int y=0; y< IRef.cols; y++) { 40 | //% point in reference image. note that the pixel-coordinates of the 41 | //% point (1,1) are actually (0,0). 42 | if (DRef.at(x,y) > 0) { 43 | 44 | Mat_ p = Mat( Point3d(x,y,1)) * DRef(x,y); 45 | //cout << "p: "; printMat(p); 46 | //% transform to image (unproject, rotate & translate) 47 | Mat_ pTrans = K * ( RKInv * p + t ); 48 | //cout << "pTrans: "; printMat(pTrans); 49 | //% if point is valid (depth > 0), project and save result. 50 | if (pTrans(2, 0) > 0 ) { 51 | int newX = (int)round(pTrans(0,0)/pTrans(2,0)); 52 | int newY = (int)round(pTrans(1,0)/pTrans(2,0)); 53 | 54 | if (newX >= 0 && newX < Img.rows && newY >= 0 && newY < Img.cols) { 55 | Img(newX,newY) = I(x,y); 56 | } 57 | } else { 58 | Img(x,y) = 0; 59 | //IRef(x,y) = 0; 60 | } 61 | 62 | } else { 63 | Img(x,y) = 0; 64 | //IRef(x,y) = 0; 65 | } 66 | } 67 | } 68 | 69 | 70 | Mat err = IRef - Img; 71 | Mat err8U; 72 | err.convertTo(err8U, CV_8U); 73 | upscaleImage(err8U, lvl); 74 | imshow("err", err8U); 75 | usleep(100); 76 | waitKey(1); 77 | Mat errLine = err.reshape(1, err.rows*err.cols); 78 | errLine.convertTo(errLine, CV_32F); 79 | 80 | return errLine.clone(); 81 | } 82 | 83 | void deriveErrNumeric(Mat IRef, Mat DRef, Mat I, Mat_ xi, Mat_ K, Mat& Jac, Mat& residual, int lvl ) { 84 | 85 | //translation 86 | float eps = 0.00195; 87 | Jac = Mat::zeros(I.rows * I.cols, 6, CV_32F); 88 | residual = calcErr(IRef,DRef,I,xi,K,lvl); 89 | for (int j=0;j<6;j++) { 90 | Mat_ epsVec = Mat::zeros(1,6, CV_32F); 91 | epsVec(0,j) = eps; 92 | //cout << "epsVec: "; printMat(epsVec); 93 | 94 | //% MULTIPLY epsilon from left onto the current estimate. 95 | Mat tmp = se3Exp(epsVec) * se3Exp(xi); 96 | Mat xiPerm = se3Log(tmp); 97 | Jac.col(j) = (calcErr(IRef,DRef,I,xiPerm,K,lvl) - residual) / eps; 98 | 99 | //printMat( xiPerm); 100 | } 101 | //printMat(Jac); 102 | } 103 | 104 | void deriveErrAnalitic(Mat_ IRef, Mat_ DRef, Mat_ I, Mat_ xi, Mat_ K, Mat_& Jac, Mat& residual, int lvl ) { 105 | Mat T = se3Exp(xi); 106 | Mat R = T(cv::Rect(0,0,3,3)); 107 | Mat t = T(cv::Rect(3,0,1,3)); 108 | 109 | Mat RKInv = R * K.inv(); 110 | 111 | //float dNaN = numeric_limits::quiet_NaN(); 112 | Mat_ Img = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 113 | Mat_ dyI, dxI; 114 | calculateGradients(I, dxI, dyI); 115 | 116 | Mat_ dxImg = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 117 | Mat_ dyImg = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 118 | 119 | Mat_ xp = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 120 | Mat_ yp = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 121 | Mat_ zp = Mat(IRef.rows, IRef.cols,CV_32F, cv::Scalar(0)); 122 | 123 | for (int x=0; x< IRef.rows; x++) { 124 | for (int y=0; y< IRef.cols; y++) { 125 | //% point in reference image. note that the pixel-coordinates of the 126 | //% point (1,1) are actually (0,0). 127 | if (DRef.at(x,y) > 0) { 128 | 129 | Mat_ p = Mat( Point3d(x,y,1)) * DRef(x,y); 130 | //cout << "p: "; printMat(p); 131 | //% transform to image (unproject, rotate & translate) 132 | Mat_ pTrans = K * ( RKInv * p + t ); 133 | //cout << "pTrans: "; printMat(pTrans); 134 | //% if point is valid (depth > 0), project and save result. 135 | if (pTrans(2, 0) > 0 ) { 136 | int newX = (int)round(pTrans(0,0)/pTrans(2,0)); 137 | int newY = (int)round(pTrans(1,0)/pTrans(2,0)); 138 | if (newX >= 0 && newX < Img.rows && newY >= 0 && newY < Img.cols) { 139 | Img(newX,newY) = I(x,y); 140 | dxImg(newX,newY) = dxI(x,y); 141 | dyImg(newX,newY) = dyI(x,y); 142 | xp(newX, newY) = pTrans(0,0); 143 | yp(newX, newY) = pTrans(1,0); 144 | zp(newX, newY) = pTrans(2,0); 145 | } 146 | } else { 147 | //Img(x,y) = 0; 148 | } 149 | 150 | } else { 151 | //Img(x,y) = 0; 152 | } 153 | } 154 | } 155 | 156 | Mat tmp; /* 157 | dxImg.convertTo(tmp, CV_8U); 158 | upscaleImage(tmp, lvl); 159 | imshow("dxImg", tmp); 160 | 161 | (dyImg.convertTo(tmp, CV_8U); 162 | upscaleImage(tmp, lvl); 163 | imshow("dyImg", tmp); 164 | 165 | Img.convertTo(tmp, CV_8U); 166 | upscaleImage(tmp, lvl); 167 | imshow("Img", tmp); 168 | 169 | waitKey(0);*/ 170 | dxImg = K(0,0) * dxImg.reshape(1, dxImg.rows*dxImg.cols); 171 | dyImg = K(1,1) * dyImg.reshape(1, dyImg.rows*dyImg.cols); 172 | 173 | //% 2.: get warped 3d points (x', y', z'). 174 | xp = xp.reshape(1, xp.rows*xp.cols); 175 | yp = yp.reshape(1, yp.rows*yp.cols); 176 | zp = zp.reshape(1, zp.rows*zp.cols); 177 | 178 | 179 | //% 3. direct implementation of kerl2012msc.pdf Eq. (4.14): 180 | 181 | Jac = Mat::zeros(Img.cols * Img.rows, 6, CV_32F); 182 | 183 | for (int i=0;i 1 && dxImg(i,0) > 5 && dyImg(i,0) > 5) { 185 | Jac(i,0) = dxImg(i,0) / zp(i,0); 186 | Jac(i,1) = dyImg(i,0) / zp(i,0); 187 | Jac(i,2) = - (dxImg(i,0) * xp(i,0) + dyImg(i,0) * yp(i,0)) / (zp(i,0) * zp(i,0)); 188 | 189 | Jac(i,3) = - (dxImg(i,0) * xp(i,0) * yp(i,0)) / (zp(i,0) * zp(i,0)) - dyImg(i,0) * (1 + (yp(i,0) / zp(i,0))*(yp(i,0) / zp(i,0))); 190 | Jac(i,4) = + dxImg(i,0) * (1 + (xp(i,0) / zp(i,0))*(xp(i,0) / zp(i,0))) + (dyImg(i,0) * xp(i,0) * yp(i,0)) / (zp(i,0) * zp(i,0)); 191 | Jac(i,5) = (- dxImg(i,0) * yp(i,0) + dyImg(i,0) * xp(i,0)) / zp(i,0); 192 | } 193 | } 194 | //i% invert jacobian: in kerl2012msc.pdf, the difference is defined the other 195 | //% way round, see (4.6). 196 | 197 | //printMat(Jac); 198 | //Jac = -Jac; 199 | Mat err = IRef - Img; 200 | Mat err8U; 201 | 202 | Img.convertTo(err8U, CV_8U); 203 | upscaleImage(err8U, lvl); 204 | imshow("err",err8U); 205 | 206 | waitKey(1); 207 | residual = err.reshape(1, err.rows*err.cols); 208 | } 209 | 210 | int main() { 211 | int lvl = LVL; 212 | 213 | float k[] = k_values; 214 | Mat_ K = Mat(3,3, CV_32F, k); 215 | Mat img1 = imread(IMAGE1, IMREAD_GRAYSCALE); 216 | Mat img2 = imread(IMAGE2, IMREAD_GRAYSCALE); 217 | 218 | imshow("orig 1: ", img1-img2); 219 | //imshow("orig 2: ", img2); 220 | 221 | Mat img1_depth = imread(IMAGE1_DEPTH, IMREAD_ANYDEPTH); 222 | Mat img2_depth = imread(IMAGE2_DEPTH, IMREAD_ANYDEPTH); 223 | 224 | img1.convertTo(img1, CV_32F); 225 | img1_depth.convertTo(img1_depth, CV_32F); 226 | img2.convertTo(img2, CV_32F); 227 | img2_depth.convertTo(img2_depth, CV_32F); 228 | Mat xi = Mat::zeros(1,6,CV_32F); 229 | //float xi_solution[] = xi_values; 230 | //Mat xi = Mat(1,6,CV_32F, xi_solution); 231 | 232 | /*Mat IRef = img1.clone(); 233 | Mat ITwo = img2.clone(); 234 | Mat DRef = img1_depth.clone(); 235 | Mat_ Klvl = K.clone();*/ 236 | 237 | 238 | //% use huber weights 239 | bool useHuber = true; 240 | 241 | //% exactly one of those should be true. 242 | bool useGN = true; //% Gauss-Newton 243 | bool useLM = false; //% Levenberg Marquad 244 | bool useGD = false; //% Gradiend descend 245 | 246 | for (;lvl>1;lvl--) { 247 | Mat IRef = img1.clone(); 248 | Mat ITwo = img2.clone(); 249 | Mat DRef = img1_depth.clone(); 250 | Mat_ Klvl = K.clone(); 251 | 252 | downscaleImage(IRef, lvl); 253 | downscaleDepth(DRef, lvl); 254 | downscaleImage(ITwo, lvl); 255 | downscaleK(Klvl, lvl); 256 | cout << lvl << endl; 257 | /* 258 | Mat_ img1 = Mat(30, 40, CV_32F, iref); 259 | Mat_ img2 = Mat(30, 40, CV_32F, isecond); 260 | Mat_ img1_depth = Mat(30, 40, CV_32F, dref); 261 | */ 262 | 263 | Mat_ Jac; 264 | Mat_ residual; 265 | 266 | Scalar errScalar; 267 | float lambda = 0.1; 268 | 269 | float err; 270 | float errLast = 1110; 271 | for (int i=0; i<10; i++) { 272 | 273 | //% calculate Jacobian of residual function (Matrix of dim (width*height) x 6) 274 | //deriveErrNumeric(IRef,DRef,ITwo,xi,Klvl, Jac, residual,lvl); 275 | deriveErrAnalitic(IRef, DRef, ITwo, xi, Klvl, Jac, residual, lvl); 276 | 277 | Mat_ huber = Mat::ones(residual.rows, 6, CV_32F); 278 | 279 | if (useHuber) { 280 | //% compute Huber Weights 281 | float huberDelta = 60; 282 | for (int j = 0; j < huber.rows; j++) { 283 | //huber(abs(residual) > huberDelta) = huberDelta ./ abs(residual(abs(residual) > huberDelta)); 284 | if ( abs(residual(j,0)) > huberDelta ) { 285 | huber.row(j) = huber.row(j)*(huberDelta / abs(residual(j,0))); 286 | } 287 | } 288 | } 289 | 290 | Mat upd; 291 | if(useGN) { 292 | upd = - ( transpose(Jac) * (huber.mul ( Jac))).inv(DECOMP_SVD)* (transpose(Jac)* ( residual.mul(huber.col(0)))); 293 | } 294 | 295 | if(useGD) { 296 | //% do gradient descend 297 | upd = - transpose( Jac) * (residual.mul(huber.col(0))); 298 | cout << "norm(upd): " << norm(upd) << endl; 299 | upd = 0.001 * upd / norm(upd); // % choose step size such that the step is always 0.001 long. 300 | 301 | } 302 | 303 | if (useLM) { 304 | //% do LM 305 | Mat H = transpose( Jac) * ( Jac.mul( huber )); 306 | //cout << "H: "; printMat( Mat::diag( H.diag())); 307 | Mat diagonal = Mat::diag( H.diag()); 308 | //cout << "H: "; printMat( ); 309 | 310 | upd = - (H + lambda * diagonal).inv(DECOMP_SVD) * (transpose( Jac) * ( residual.mul(huber.col(0)))); 311 | } 312 | 313 | //cout <<"upd: "; printMat(upd); 314 | 315 | //% MULTIPLY increment from left onto the current estimate. 316 | Mat lastXi; 317 | lastXi = xi.clone(); 318 | 319 | xi = se3Log(se3Exp(upd) * se3Exp(xi)); 320 | cout <<"updated Xi: "; printMat(xi); 321 | //% get mean and display 322 | float sumErr = 0; 323 | Mat_ resid2 = residual.clone(); 324 | for (int item=0; item= errLast) { 337 | lambda = lambda * 5; 338 | xi = lastXi; 339 | 340 | if(lambda > 5) { 341 | break; 342 | } 343 | else { 344 | lambda = lambda /1.5; 345 | } 346 | } 347 | } 348 | if(useGN || useGD) { 349 | if(err / errLast > 0.995) { 350 | break; 351 | } 352 | } 353 | } 354 | } 355 | /////-------------------------- 356 | 357 | //upscaleImage(err,lvl); 358 | Mat T = se3Exp(xi); 359 | Mat R = T(cv::Rect(0,0,3,3)); 360 | Mat t = T(cv::Rect(3,0,1,3)); 361 | cout << "Final R: "; printMat( R); 362 | cout << "Final t: "; printMat(t); 363 | 364 | waitKey(0); 365 | /*cout<< "Image1: "; printType(img1); 366 | cout<< "Image1 depth: "; printType(img1_depth); 367 | 368 | vector points_proj; 369 | 370 | for (int i=0; i< img1.rows;i++) { 371 | for(int j=0; j < img1.cols;j++) { 372 | char depth = img1_depth.at(i,j); 373 | if (depth > 0) { 374 | points_proj.push_back(Point3f(i, j, depth)); 375 | } 376 | } 377 | } 378 | 379 | Mat colors(1,points_proj.size(), CV_8UC3); 380 | for (int i=0;i(0,i) = img1.at((int)points_proj[i].x, (int)points_proj[i].y); 382 | } 383 | 384 | viz::WCloud cloud_widget = viz::WCloud( points_proj, colors ); 385 | cloud_widget.setRenderingProperty( cv::viz::POINT_SIZE, 2 ); 386 | viz::Viz3d trajectoryWindow("show"); 387 | 388 | trajectoryWindow.showWidget("point_cloud", cloud_widget); 389 | 390 | trajectoryWindow.spin();*/ 391 | 392 | return 0; 393 | } 394 | -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/rgb/1305031102.175304.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/rgb/1305031102.175304.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/rgb/1305031102.275326.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/rgb/1305031102.275326.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/rgb/1341847980.722988.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/rgb/1341847980.722988.png -------------------------------------------------------------------------------- /exercise9-dirct-methods-2/rgb/1341847982.998783.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/smitherson/mvg-exercises/fcc5e891269c91d2fca1bcc01ea145842677bd86/exercise9-dirct-methods-2/rgb/1341847982.998783.png --------------------------------------------------------------------------------