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More Robust Face Recognition by Considering Occlusion Information
Citation key 1155Rama2008
Author Antonio Rama and Lutz Goldmann and Francesc Tarres and Thomas Sikora
Title of Book 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2008, Amsterdam, The Netherlands
Year 2008
Address Amsterdam, Netherlands
Month sep
Note Poster?
Editor Jeffrey F. Cohn, Thomas S. Huang, Maja Pantic, Nicu Sebe, Ferdinand Beljaars
Publisher IEEE Press
Organization IEEE FG
Abstract This paper addresses one of the main challenges of face recognition (FR): facial occlusions. Currently, the human brain is the most robust known FR approach towards partially occluded faces. Nevertheless, it is still not clear if humans recognize faces using a holistic or a component-based strategy, or even a combination of both. In this paper, three different approaches based on Principal Component Analysis (PCA) are analyzed. The first one, a holistic approach, is the well-known Eigenface approach. The second one, a component-based method, is a variation of the Eigen-features approach, and finally, the third one, a near-holistic method, is an extension of the Lophoscopic Principal Component Analysis (LPCA). So the main contributions of this paper are: The three different strategies are compared and analyzed for identifying partially occluded faces and furthermore it explores how a priori knowledge about present occlusions can be used to improve the recognition performance.
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