Journal
PATTERN RECOGNITION
Volume 45, Issue 9, Pages 3131-3140Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2011.10.017
Keywords
Image warping; Face recognition; Energy minimization
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This paper systematically analyzes the strengths and weaknesses of existing image warping algorithms on the tasks of face recognition. Image warping is used to cope with local and global image variability and in general is an NP-complete problem. Although many approximations have recently been proposed, neither thorough comparison, nor systematic analysis of methods in a common scheme has been done so far. We follow the bottom-up approach and analyze the methods with increasing degree of image structure preserved during optimization. We evaluate the presented warping approaches on four challenging face recognition tasks in highly variable domains. Our findings indicate that preserving maximum dependencies between neighboring pixels by imposing strong geometrical constraints leads to the best recognition results while making optimization efficient. (C) 2011 Elsevier Ltd. All rights reserved.
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