CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Partial Face Recognition: Alignment-Free Approach
Liao, Shengcai1,2; Jain, Anil K.3; Li, Stan Z.1,2
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
2013-05-01
Volume35Issue:5Pages:1193-1205
SubtypeArticle
AbstractNumerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment.
KeywordPartial Face Recognition Alignment Free Keypoint Descriptor Sparse Representation Open-set Identification
WOS HeadingsScience & Technology ; Technology
WOS KeywordPARTIAL OCCLUSION ; ROBUST ; SELECTION ; MODELS ; SCALE ; REPRESENTATION ; FEATURES ; SPARSE ; IMAGES
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000316126800013
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7948
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Ctr Biometr & Secur Res, Inst Automat, Beijing 100190, Peoples R China
3.Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA
Recommended Citation
GB/T 7714
Liao, Shengcai,Jain, Anil K.,Li, Stan Z.. Partial Face Recognition: Alignment-Free Approach[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2013,35(5):1193-1205.
APA Liao, Shengcai,Jain, Anil K.,&Li, Stan Z..(2013).Partial Face Recognition: Alignment-Free Approach.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,35(5),1193-1205.
MLA Liao, Shengcai,et al."Partial Face Recognition: Alignment-Free Approach".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 35.5(2013):1193-1205.
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