Face recognition with learning-based descriptor
文献类型：会议论文
| 作者 | Zhimin Cao; Qi Yin; Xiaoou Tang; Jian Sun |
| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：深圳先进技术研究院
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