├── AdaBoost.m ├── AdaBoostClassfy.m ├── ExtractAndTrain.m ├── IntegralImage.m ├── MoveWindowing.m ├── ThreshSegement.m ├── calDetectRate.m ├── geneStdDisImage.m ├── getStdDisImage.m ├── testHarrLikeFea.m ├── testMWSegment.m ├── LabelDetectWindow.m ├── dispCombineImage.m ├── MultiThreshSegement.m ├── calPredictErrorRate.m ├── dispWindowingResult.m ├── extHarrLikeFeature.m ├── testAdaBoostLearner.m ├── trainAdaBoostLearner.m ├── searchBestWeakLearner.m ├── CalPixelFrequencyInWindow.m ├── ImageBlockRecogByAdaBoost.m ├── AdaBoostWeakLearnerClassfy.m ├── AdaBoostDecisionForImageBlock.m ├── ImageBlockRecogByCascadeAdaBoost.m └── README.md /AdaBoost.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cuijiaxun/FaceRecognitionByMatlab/HEAD/AdaBoost.m -------------------------------------------------------------------------------- /AdaBoostClassfy.m: 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This program is based on the Adaboost Algorithm and Haar Feature 3 | 背景阐述 4 | 开发一个纯Matlab下的人脸识别系统其实非常有益，因为Matlab具有极强的图像处理功能。然而目前互联网上大多采用OpenCV＋C++编译Matlab API的方法进行Matlab人脸识别，我觉得这是完全没有意义的。因此，我选择理解Viola－Jones提出的人脸识别算法，并仅用Matlab进行编程。 5 | 6 | 1.1主要文件及作用 7 | 8 | 测试训练及提取特征：运行ExtractAndTrain.m（不建议低gpu配置运行） 9 | 测试检测性能：运行testMWSegment.m 10 | 11 | 数据库 12 | faces文件夹 13 | 4422张人脸 14 | 正样本 15 | nonfaces文件夹 16 | 4381张非人脸 17 | 负样本 18 | 主程序1 19 | （特征提取及训练） 20 | ExtractAndTrain.m 21 | 提取和训练的主程序 22 | （建议不要跑，训练要7小时左右） 23 | 定义了Haar特征，提取特征，训练，错误率计算 24 | 特征提取函数 25 | integralImage.m 26 | 求积分图像 27 | 28 | extHarrLikeFeature.m 29 | 提取Harr-like特征 30 | 31 | 训练所需要的函数 32 | trainAdaBoostLearner.m 33 | 训练100个强分类器，找到区别人脸的阈值 34 | 35 | searchBestWeakLearner.m 36 | 根据错误率找到最好的weak learner 37 | 38 | AdaBoostClassfy.m 39 | 强学习分类 40 | 41 | calPredictErrorRate.m 42 | 计算错误概率 43 | 44 | testAdaBoostLearner.m 45 | 自我循环样本，测试误判 46 | 47 | 数据库 48 | HarrLikeFeatures-2.mat 49 | 保存提取的特征及训练数据 50 | 可以直接使用作为数据库 51 | 52 | 主函数2 53 | 图像检测 54 | testMWSegment.m 55 | 窗口检测程序 56 | 指定判断算法、窗口数据、划定网格 57 | 判断函数 58 | MoveWindowing.m 59 | 移动窗口、放缩 60 | 61 | ImageBlockRecogByAdaBoost.m 62 | 对当前窗口进行识别 63 | 64 | ThreshSegement.m 65 | 阈值分割 66 | 67 | LabelDetectWindow.m 68 | 给找到的图像进行加框 69 | 70 | 级联检测 71 | ImageBlockRecogByCascadeAdaBoost.m 72 | 级联检测 73 | 就写了一下，还没有整合进程序 74 | --------------------------------------------------------------------------------