MATEC Web of Conferences
Volume 44, 20162016 International Conference on Electronic, Information and Computer Engineering
|Number of page(s)||4|
|Section||Computer, Algorithm, Control and Application Engineering|
|Published online||08 March 2016|
Robust Face Recognition via Occlusion Detection and Masking
College of Communication Engineering, Chongqing University, 400044, Chongqing, China
a Zhu hongqin: email@example.com
Sparse representation-based classification (SRC) method has demonstrated promising results in face recognition (FR). In this paper, we consider the problem of face recognition with occlusion. In sparse representation-based classification method, the reconstruction residual of test sample over the training set is usually heterogeneous with the training samples, highlighting the occlusion part in test sample. We detect the occlusion part by extracting a mask from the reconstruction residual through threshold operation. The mask will be applied in the representation-based classification framework to eliminate the impact of occlusion in FR. The method does not assume any prior knowledge about the occlusion, and extensive experiments on publicly available databases show the efficacy of the method.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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