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Incremental Learning of Patch-based Bag of Facial Words Representation for Online Face Recognition in Videos
Chao Wang; Yunhong Wang; Zhaoxiang Zhang
2012-12-04
Conference NamePacific-Rim Conference on Multimedia
Source PublicationPCM 2012
Conference Date4-6 December 2012
Conference PlaceSingapore, Singapore
AbstractVideo-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.
KeywordVideo Analysis Face Recognition Biometrics Incremental Learning Bag Of Words
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13259
Collection类脑智能研究中心
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
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],2012.
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