Face Tracking and Recognition via Incremental Local Sparse Representation
文献类型：会议论文
| 作者 | Chao Wang ; Yunhong Wang; Zhaoxiang Zhang; Yiding Wang
|
| 出版日期 | 2013-07-26 |
| 会议日期 | 26-28 July 2013 |
| 会议地点 | Qingdao, China |
| 关键词 | Video Analysis Face Recognition Face Tracking Video-based Face Recognition |
| 英文摘要 | This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. We first develop a robust face tracking algorithm based on the local sparse appearance. This sparse representation model exploits both partial and spatial information of the face based on a covariance pooling method. Following in the face recognition stage, with the employment of a novel template update strategy, our recognition algorithm adapts the template to appearance change and reduces the influence of occlusion and illumination variation. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database. Our proposed method produces a high face recognition results on over 93% of all videos. The tracking results on challenging videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. On the challenging data set in which faces are undergo occlusion and illumination variation, our proposed method also consistently demonstrates a high recognition rate. |
| 会议录 | ICIG 2013
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13289]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Zhaoxiang Zhang |
| 推荐引用方式 GB/T 7714 | Chao Wang,Yunhong Wang,Zhaoxiang Zhang,et al. Face Tracking and Recognition via Incremental Local Sparse Representation[C]. 见:. Qingdao, China. 26-28 July 2013. |
入库方式： OAI收割
来源：自动化研究所
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