Face Detection and Tracking Based on Adaboost CamShift and Kalman Filter Algorithm

被引：0

作者：

Chen, Kun ^{[1
]}

Liu, ChunLei ^{[1
]}

Xu, Yongjin ^{[1
]}

机构：

[1] Shanghai Univ, Coll Mechatron Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

来源：

COMPUTATIONAL INTELLIGENCE, NETWORKED SYSTEMS AND THEIR APPLICATIONS | 2014年 / 462卷

关键词：

Adaboost; CamShift; Kalman; face detection and tracking; OBJECT TRACKING;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Face detection is an important component of the intelligent video surveillance system. Based on the MeanShift algorithm, we have developed into the CamShift algorithm. Although the traditional Camshift algorithm can track the moving object well, it has to set the tracking object by manually. Meanwhile it fails to track the object easily while the object is occluded and interfered by the same color obstructions. In order to solve the problem, according to the CamShift algorithm features, in this article, I will combine Adaboost, CamShift and Kalman filtering algorithm, which can be relied on to realize face detection and tracking automatically and accurately.

引用

页码：149 / 158

页数：10

共 50 条

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Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai
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