how to draw Opencv face detection Adaboost ROC/PR (绘制方法)

关于adaboost的一些说明 cf.http://www.opencv.org.cn/forum/viewtopic.php?t=4264

Rainer Lienhart, Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection: Receiver Operating Curves (ROCs) were constructed by varying the required number of detected faces per actual face
before merging into a single detection result.

An Extended Set of Haar-like Features for Rapid Object Detection: We can easily construct an non-optimal ROC by smoothly varying offset b.

PAUL VIOLA. Robust Real-Time Face Detection: To create the ROC curve the threshold of the perceptron on the final layer classifier is adjusted from+∞to−∞.
Adjusting the threshold to +∞will yield a detection rate of 0.0 and a false positive rate of 0.0. Adjusting the threshold to−∞, however, increases both the detection rate and
false positive rate, but only to a certain point. Neither rate can be higher than the rate of the detection cascade minus the final layer. In effect, a threshold of−∞ is equivalent to removing that layer. Further increasing
the detection and false positive rates requires decreasing the threshold of the next classifier in the cascade. Thus, in order to construct a complete ROC curve, classifier layers are removed.

生成Opencv的人脸检测的ROC曲线方法

通过在void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& objects, vector <int>&rejectLevels,vector<double>&levelWeights, double scaleFactor, int minNeighbors, int flags, Size minObjectSize, Size maxObjectSize, bool outputRejectLevels )中提供空的rejectLevels
和levelWeights以及设置outputRejectLevels为true，可以得到含有分数的检测结果（调用了cvHaarDetectObjectsForROC()方法生成），但是这种数据在FDDB[6]的衡量标准下曲线还挺正常，但是在VOC DevKit下的曲线就病态了（对于alt，alt2，alt-tree，default都是这样）。所以最好的办法还是修改CascadeClassifier的cascade level number and stage threshold, 对于Opencv中自带的五个cascade
classifier，如profile face和alt, alt2, default，可以通过设置cascade level和stage threshold（NOTE: cascadeClassifier> oldCascade->hid_cascade->stage_classifier>threshold）来生成测试数据，对于alt_tree，只设置stage threshold 就好了，然后用DevKit的matlab 代码生成多个（precision, recall）点，这样就可以绘制PR曲线了。

1. Xiangxin Zhu, Deva Ramanan. Face Detection, Pose Estimation, and Landmark Localization in the Wild. CVPR. 2012.http://www.ics.uci.edu/~xzhu/face/

2. Rainer Lienhart. Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection.

3. Rainer Lienhart. An Extended Set of Haar-like Features for Rapid Object Detection.

4. Wang Qiang. Part-based Object Detection for Real-time Systems.

5. UltraCompare Pro(文件内容对比工具) 8.30.0.1003. http://www.downxia.com/downinfo/1287.html

6. V. Jain and E. Learned-Miller. Fddb: A benchmark for face detection in unconstrained settings. Technical Report UMCS- 2010-009, UMass, Amherst, 2010.http://vis-www.cs.umass.edu/fddb/

转载来自：http://blog.csdn.net/pobudeyi/article/details/8196699