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	Face recognition with learning-based descriptor
	Zhimin Cao; Qi Yin; Xiaoou Tang; Jian Sun
	2010
会议名称	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
会议地点	San Francisco, CA
英文摘要	We present a novel approach to address the representation issue and the matching issue in face recognition (verification). Firstly, our approach encodes the micro-structures of the face by a new learning-based encoding method. Unlike many previous manually designed encoding methods (e.g., LBP or SIFT), we use unsupervised learning techniques to learn an encoder from the training examples, which can automatically achieve very good tradeoff between discriminative power and invariance. Then we apply PCA to get a compact face descriptor. We find that a simple normalization mechanism after PCA can further improve the discriminative ability of the descriptor. The resulting face representation, learning-based (LE) descriptor, is compact, highly discriminative, and easy-to-extract. To handle the large pose variation in real-life scenarios, we propose a pose-adaptive matching method that uses pose-specific classifiers to deal with different pose combinations (e.g., frontal v.s. frontal, frontal v.s. left) of the matching face pair. Our approach is comparable with the state-of-the-artmethods on the Labeled Face in Wild (LFW) benchmark (we achieved 84.45% recognition rate), while maintaining excellent compactness, simplicity, and generalization ability across different datasets
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/2760]
专题	深圳先进技术研究院_集成所
作者单位	2010
推荐引用方式 GB/T 7714	Zhimin Cao,Qi Yin,Xiaoou Tang,et al. Face recognition with learning-based descriptor[C]. 见:2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. San Francisco, CA.

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