A depth cascade face detection algorithm based on adaboost
Wenxiang Yu, Jiapeng Xiu, Chen Liu, Zhengqiu Yang · 2016
In this paper, a face detection algorithm based on AdaBoost algorithm combined with Haar classifier depth cascade about OpenCV is proposed. In order to solve the problem that the training depth of AdaBoost algorithm is not enough and the Haar classifier is not accurate because of the lack of depth cascade classification. Before the face feature extraction, AdaBoost algorithm is used to train the face samples to train the strong classifier. Then using OpenCV Haar classifier to depth classification for these strong classifier, it equal to cascade the AdaBoost algorithm, using high efficiency characteristic matrix and integral image method to accelerate the extraction rate of image feature values of the Haar-like.