Local dual closed loop model based Bayesian face tracking

被引：0

作者：

Yao, Dan ^{[1
]}

Lu, Hong ^{[1
]}

Xue, Xiangyang ^{[1
]}

Zhou, Zhongyi ^{[1
]}

机构：

[1] Fudan Univ, Dept Comp Sci & Engn, Shanghai 200433, Peoples R China

来源：

ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2007 | 2007年 / 4810卷

关键词：

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 paper presents a new Bayesian face tracking method under particle filter framework. First, two adaptive feature models are proposed to extract face features from image sequences. Then the robustness of face tracking is reinforced via building a local dual closed loop model (LDCLM). Meanwhile, trajectory analysis, which helps to avoid unnecessary restarting of detection module, is introduced to keep tracked faces' identity as consistent as possible. Experimental results demonstrate the efficacy of our method.

引用

页码：98 / +

页数：2

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