Abstract-The term periocular refers to the facial region in the immediate vicinity of the eye. Acquisition of the periocular biometric is expected to require less subject cooperation while permitting a larger depth of field compared to traditional ocular biometric traits (viz., iris, retina, and sclera). In this work, we study the feasibility of using the periocular region as a biometric trait. Global and local information are extracted from the periocular region using texture and point operators resulting in a feature set for representing and matching this region. A number of aspects are studied in this work, including the 1) effectiveness of incorporating the eyebrows, 2) use of side information (left or right) in matching, 3) manual versus automatic segmentation schemes, 4) local versus global feature extraction schemes, 5) fusion of face and periocular biometrics, 6) use of the periocular biometric in partially occluded face images, 7) effect of disguising the eyebrows, 8) effect of pose variation and occlusion, 9) effect of masking the iris and eye region, and 10) effect of template aging on matching performance. Experimental results show a rank-one recognition accuracy of 87.32% using 1136 probe and 1136 gallery periocular images taken from 568 different subjects (2 images/subject) in the Face Recognition Grand Challenge (version 2.0) database with the fusion of three different matchers.
Another interesting work REF , which is an extension of the first paper, has extensively presented results with various aspects of periocular recognition that include role of eyebrows, left or right eye information contribution, manual or automatic segmentation impacts, local and global feature's effectiveness, performance achieved by fusion with face and periocular biometrics, degradation due to partial occlusion over face images, effect of disguising the eyebrows, effect of masking the iris and eye region and analyzing the effect of pose variation and occlusion.
Periocular Biometrics in the Visible Spectrum
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Forensics and Security
Computer Science