NDLI: Synthetic face generation under various operational conditions in video surveillance

Content Provider	IEEE Xplore Digital Library
Author	Mokhayeri, F. Granger, E. Bilodeau, G.-A.
Copyright Year	2015
Description	Author affiliation: LITIV, Polytech. Montreal, Montréal, QC, Canada (Bilodeau, G.-A.) \|\| LIVIA, Univ. du Quebec, Montréal, QC, Canada (Mokhayeri, F.; Granger, E.)
Abstract	In still-to-video face recognition (FR), the faces captured with surveillance cameras are matched against reference stills of target individuals enrolled to the system. FR is a challenging problem in video surveillance due to uncontrolled capture conditions (variations in pose, expression, illumination, blur, scale, etc.), and the limited number of reference stills to model target individuals. This paper introduces a new approach to generate multiple synthetic face images per reference still based on camera-specific capture conditions to deal with illumination variations. For each reference still, a diverse set of faces from non-target individuals appearing in the camera viewpoint are selected based on luminance and contrast distortion. These face images are then decomposed into detail layer and large scale layer using an edge-preserving image decomposition to obtain their illumination dependent component. Finally, the large scale layers of these images are morphed with each reference still image to generate multiple synthetic reference stills that incorporate illumination and contrast conditions. Experimental results obtained with the ChokePoint dataset reveal that these synthetic faces produce an enhanced face model. As the number of synthetic faces grows, the proposed approach provides a higher level of accuracy and robustness across a range of capture conditions.
Starting Page	4052
Ending Page	4056
File Size	1069082
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351567
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face Lighting Cameras Video surveillance Image edge detection Feature extraction Face recognition Synthetic face generation Video Surveillance Face Recognition Image Morphing
Content Type	Text
Resource Type	Article

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