A DEPTH CASCADE FACE DETECTION ALGORITHM BASED ON ADABOOST

被引：0
|
作者：
Yu, Wenxiang [1 ]
Xiu, Jiapeng [1 ]
Liu, Chen [1 ]
Yang, Zhengqiu [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
来源：
PROCEEDINGS OF 2016 5TH IEEE INTERNATIONAL CONFERENCE ON NETWORK INFRASTRUCTURE AND DIGITAL CONTENT (IEEE IC-NIDC 2016) | 2016年
关键词：
Face detection; AdaBoost algorithm; Haar classifier; Characteristic matrix; Integral image;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：103 / 107
页数：5
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