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Patch-based Bag of Features for Face Recognition in Videos
Chao Wang; Yunhong Wang; Zhaoxiang Zhang
2012-12-04
会议名称Chinese Conference on Biometric Recognition
会议录名称CCBR 2012
会议日期4-5 December 2012
会议地点Guangzhou, China
摘要Video-based face recognition is a fundamental topic in image processing and video representation, and presents various challenges and opportunities. In this paper, we introduce an efficient patch-based bag of features (PBoF) method to video-based face recognition that plenty exploits the spatiotemporal information in videos, and does not make any assumptions about the pose, expressions or illumination of face. First, descriptors are used for feature extraction from patches, then with the quantization of a codebook, each descriptor is converted into code. Next, codes from each region are pooled together into a histogram. Finally, representation of the image is generated by concatenating the histograms from all regions, which is employed to do the categorization. In our experiments, 100% recognition rate is achieved on the Honda/UCSD database, which outperforms the state of the arts. And from the theoretical and experimental results, it can be derived that, when choosing a single descriptor and no prior knowledge about the data set and object is available, the dense SIFT with ScSPM is recommended. Experimental results demonstrate the effectiveness and flexibility of our proposed method.
关键词Face Recognition Video-based Face Recognition Bag Of Feature Sparse Coding
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13258
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. Patch-based Bag of Features for Face Recognition in Videos[C],2012.
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