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The Scientific World Journal
Volume 2014 (2014), Article ID 519158, 10 pages
Research Article

Efficient Detection of Occlusion prior to Robust Face Recognition

1Department of Multimedia Communications, EURECOM, 450 Route des Chappes, 06410 Biot, France
2Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, P.O. Box 4500, 90014 Oulu, Finland

Received 26 August 2013; Accepted 7 October 2013; Published 16 January 2014

Academic Editors: S. Berretti, S. Hong, and T. Yamasaki

Copyright © 2014 Rui Min et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


While there has been an enormous amount of research on face recognition under pose/illumination/expression changes and image degradations, problems caused by occlusions attracted relatively less attention. Facial occlusions, due, for example, to sunglasses, hat/cap, scarf, and beard, can significantly deteriorate performances of face recognition systems in uncontrolled environments such as video surveillance. The goal of this paper is to explore face recognition in the presence of partial occlusions, with emphasis on real-world scenarios (e.g., sunglasses and scarf). In this paper, we propose an efficient approach which consists of first analysing the presence of potential occlusion on a face and then conducting face recognition on the nonoccluded facial regions based on selective local Gabor binary patterns. Experiments demonstrate that the proposed method outperforms the state-of-the-art works including KLD-LGBPHS, S-LNMF, OA-LBP, and RSC. Furthermore, performances of the proposed approach are evaluated under illumination and extreme facial expression changes provide also significant results.