Multi-Task Pose-Invariant Face Recognition

doi:10.1109/TIP.2015.2390959

CORC > 北京大学 > 信息科学技术学院

	Multi-Task Pose-Invariant Face Recognition
	Ding, Changxing ; Xu, Chang ; Tao, Dacheng
刊名	IEEE Transactions on Image Processing
	2015
DOI	10.1109/TIP.2015.2390959
英文摘要	Face images captured in unconstrained environments usually contain significant pose variation, which dramatically degrades the performance of algorithms designed to recognize frontal faces. This paper proposes a novel face identification framework capable of handling the full range of pose variations within ±90° of yaw. The proposed framework first transforms the original pose-invariant face recognition problem into a partial frontal face recognition problem. A robust patch-based face representation scheme is then developed to represent the synthesized partial frontal faces. For each patch, a transformation dictionary is learnt under the proposed multi-task learning scheme. The transformation dictionary transforms the features of different poses into a discriminative subspace. Finally, face matching is performed at patch level rather than at the holistic level. Extensive and systematic experimentation on FERET, CMU-PIE, and Multi-PIE databases shows that the proposed method consistently outperforms single-task-based baselines as well as state-of-the-art methods for the pose problem. We further extend the proposed algorithm for the unconstrained face verification problem and achieve top-level performance on the challenging LFW data set. ? 2015 IEEE.; EI; 3; 980-993; 24
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436049]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Ding, Changxing,Xu, Chang,Tao, Dacheng. Multi-Task Pose-Invariant Face Recognition[J]. IEEE Transactions on Image Processing,2015.
APA	Ding, Changxing,Xu, Chang,&Tao, Dacheng.(2015).Multi-Task Pose-Invariant Face Recognition.IEEE Transactions on Image Processing.
MLA	Ding, Changxing,et al."Multi-Task Pose-Invariant Face Recognition".IEEE Transactions on Image Processing (2015).