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Tracking and recognition face in videos with incremental local sparse representation model
Chao Wang; Yunhong Wang; Zhaoxiang Zhang
2013-10-21
发表期刊Optical Engineering
卷号52期号:10页码:103-112
摘要This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.
关键词Video Databases Facial Recognition Systems
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13214
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
GB/T 7714
Chao Wang,Yunhong Wang,Zhaoxiang Zhang. Tracking and recognition face in videos with incremental local sparse representation model[J]. Optical Engineering,2013,52(10):103-112.
APA Chao Wang,Yunhong Wang,&Zhaoxiang Zhang.(2013).Tracking and recognition face in videos with incremental local sparse representation model.Optical Engineering,52(10),103-112.
MLA Chao Wang,et al."Tracking and recognition face in videos with incremental local sparse representation model".Optical Engineering 52.10(2013):103-112.
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