Incremental Learning of Patch-based Bag of Facial Words Representation for Online Face Recognition in Videos
文献类型：会议论文
| 作者 | Chao Wang ; Yunhong Wang; Zhaoxiang Zhang
|
| 出版日期 | 2012-12-04 |
| 会议日期 | 4-6 December 2012 |
| 会议地点 | Singapore, Singapore |
| 关键词 | Video Analysis Face Recognition Biometrics Incremental Learning Bag Of Words |
| 英文摘要 | Video-based face recognition is a fundamental topic in image processing and video analysis, and presents various challenges and opportunities. In this paper, we introduce an incremental learning approach to video-based face recognition which efficiently exploits the spatiotemporal information in videos. Face image sequences are incrementally clustered based on their descriptors, and the representative face images of each cluster are picked out. The incremental algorithm of creating facial visual words is applied to construct a codebook using the descriptors of the representative face images. Continuously, with the quantization of the facial visual words, each descriptor extracted from patches is converted into codes, and codes from each region are pooled together into a histogram. The representation of the face image is generated by concatenating the histograms from all regions, which is employed to perform the categorization. In the online recognition, a similarity score matrix and a voting algorithm are employed to judge a face video’s identity. Recognition is performed online while face video sequence is continuous and the proposed method gives nearly realtime feedback. The proposed method achieves a 100 % verification rate on the Honda/UCSD database and 82 % on the YouTube datebase. Experimental results demonstrate the effectiveness and flexibility of the proposed method. |
| 会议录 | PCM 2012
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13259]  |
| 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. Incremental Learning of Patch-based Bag of Facial Words Representation for Online Face Recognition in Videos[C]. 见:. Singapore, Singapore. 4-6 December 2012. |
入库方式： OAI收割
来源：自动化研究所
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