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Generalized elastic graph matching for face recognition
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AI
DOI：10.1016/j.patrec.2007.01.003.png)
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Abstract
En 中文
Elastic graph matching (EGM) is a well-known approach in face recognition area for the robust face recognition to a rotation in depth and facial expression change. We extended the conventional EGM to the generalized EGM (G-EGM), which is afford to handle even globally warped faces, by enhancing the robustness of node descriptors to a global warping, and introducing warping-compensated edges in graph matching cost function. The improved performance of the G-EGM was evaluated through the recognition simulation based on arbitrary posed faces. (c) 2007 Elsevier B.V. All rights reserved.
Keywords:
face recognition
face alignment
elastic graph matching
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