期刊
PATTERN RECOGNITION
卷 46, 期 5, 页码 1511-1521出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2012.10.025
关键词
Pose-robust face recognition; Pose-normalization; Face synthesis; Sparse representation; Latent sparse modeling
资金
- Natural Science Foundation [60872145, 60903126]
- National High-Tech. [2009AA01Z315]
- Cultivation fund from Ministry of Education of China [708085]
- Excellent Doctorate Foundation of Northwestern Polytechnical University
We propose a pose-robust face recognition method to handle the challenging task of face recognition in the presence of large pose difference between gallery and probe faces. The proposed method exploits the sparse property of the representation coefficients of a face image over its corresponding view-dictionary. By assuming the representation coefficients are invariant to pose, we can synthesize for the probe image a novel face image which has smaller pose difference with the gallery faces. Furthermore, face recognition in the presence of pose variations is achieved based on the synthesized face image again via sparse representation. Extensive experiments on CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据