On Using Gait to Enhance Frontal Face Extraction

Visual surveillance finds increasing deployment for monitoring urban environments. Operators need to be able to determine identity from surveillance images and often use face recognition for this purpose. In surveillance environments, it is necessary to handle pose variation of the human head, low f...

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Bibliographic Details
Published in:IEEE transactions on information forensics and security 2012-12, Vol.7 (6), p.1802-1811
Main Authors: Sung-Uk Jung, Nixon, M. S.
Format: Article
Language:English
Subjects:
Biometrics
Face recognition
front face extraction
gait trajectory
head pose estimation
Image resolution
looming effect
Solid modeling
Surveillance
Trajectory
Visualization
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Summary:Visual surveillance finds increasing deployment for monitoring urban environments. Operators need to be able to determine identity from surveillance images and often use face recognition for this purpose. In surveillance environments, it is necessary to handle pose variation of the human head, low frame rate, and low resolution input images. We describe the first use of gait to enable face acquisition and recognition, by analysis of 3-D head motion and gait trajectory, with super-resolution analysis. We use region- and distance-based refinement of head pose estimation. We develop a direct mapping to relate the 2-D image with a 3-D model. In gait trajectory analysis, we model the looming effect so as to obtain the correct face region. Based on head position and the gait trajectory, we can reconstruct high-quality frontal face images which are demonstrated to be suitable for face recognition. The contributions of this research include the construction of a 3-D model for pose estimation from planar imagery and the first use of gait information to enhance the face extraction process allowing for deployment in surveillance scenarios.
ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2012.2218598