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Journal of Electronic Imaging

Varying face occlusion detection and iterative recovery for face recognition
Author(s): Meng Wang; Zhengping Hu; Zhe Sun; Shuhuan Zhao; Mei Sun
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Paper Abstract

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Paper Details

Date Published: 16 May 2017
PDF: 8 pages
J. Electron. Imag. 26(3) 033009 doi: 10.1117/1.JEI.26.3.033009
Published in: Journal of Electronic Imaging Volume 26, Issue 3
Show Author Affiliations
Meng Wang, Yanshan Univ. (China)
Taishan Univ. (China)
Zhengping Hu, Yanshan Univ. (China)
Zhe Sun, Yanshan Univ. (China)
Shuhuan Zhao, Hebei Univ. (China)
Mei Sun, Taishan Univ. (China)

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