Real-time Face Tracking Algorithm Based on Adaboost and Improved Camshift

被引：0
|
作者：
Li, Yao-Hua [1 ]
You, Feng [1 ]
Chen, Kang [1 ]
Huang, Ling [1 ]
Xu, Jian-Min [1 ]
机构：
[1] South China Univ Technol, Sch Civil Engn & Transportat, Guangzhou, Guangdong, Peoples R China
来源：
2015 INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND INFORMATION SYSTEM (SEIS 2015) | 2015年
关键词：
Haar-like Feature; Cascade Classifier; Face Detection; Camshift;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This study is conducted to overcome shortages of traditional face tracking algorithm such as can't conduct automatic tracking, bad robustness in the tracking procedure, and fails when occlusion or skin-color interference occurs. For this purpose, we propose an improved Camshift algorithm to solve the problems above, and improve the performance of our system by introducing an extended Haar-like feature based Adaboost algorithm. This paper presents a novel tracking method for face tracking and detection, experimental results show that this method has good real-time performance, and performed well when occlusion, tilt, or skin-color interference occurs.
引用
收藏
页码：67 / 74
页数：8
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