DocumentCode :
39432
Title :
Partial Face Recognition: Alignment-Free Approach
Author :
Shengcai Liao ; Jain, Anubhav K. ; Li, Stan Z.
Author_Institution :
Center for Biometrics & Security Res., Inst. of Autom., Beijing, China
Volume :
35
Issue :
5
fYear :
2013
fDate :
May-13
Firstpage :
1193
Lastpage :
1205
Abstract :
Numerous 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.
Keywords :
Gabor filters; face recognition; principal component analysis; GTP; Gabor ternary pattern; LBP; MKD; PCA+LDA; alignment-free approach; an alignment-free face representation method; arbitrary patch; baseline algorithms; discriminative face recognition; face image; general partial face recognition approach; holistic face recognition; impressive performance; multikeypoint descriptors; probe face image; public domain face databases; surveillance cameras; Detectors; Face; Face recognition; Histograms; Image edge detection; Lighting; Robustness; Partial face recognition; alignment free; keypoint descriptor; open-set identification; sparse representation; Algorithms; Biometric Identification; Databases, Factual; Face; Humans; Image Processing, Computer-Assisted; Posture;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2012.191
Filename :
6296663
Link To Document :
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