A multiple-steps linear representation based classification for face recognition

Tao Liu; Jian-Xun Mi

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A multiple-steps linear representation based classification for face recognition

Tao Liu 1,Jian-Xun Mi 2 *

1.Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065

2. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065

*Correspondence author

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Funding: This work was supported partially by the National Nature Science Foundation of China under Grant Nos. 61202276. And partially this research is（No.the project No. is cstc2014jcyjA40018) and by Chongqing education committee under Grant No. KJ1500402）

Opened online:26 February 2016

Accepted by: none

Citation: Tao Liu,Jian-Xun Mi.A multiple-steps linear representation based classification for face recognition[OL]. [26 February 2016] http://en.paper.edu.cn/en_releasepaper/content/4676937

Error detection is an important approach to improve the robustness of face recognition (FR) method. However, it is hard to directly detect the outliers in a facial image. We decompose the hard problem into many simpler sub-problems in this paper. That is, the process of detecting distorted pixels is divided into multiple easier steps and a part of invalid pixels are detected in every step. The goal is to decrease the ratio of outlier in the testing image, which reduces the influence of outliers in a recognition process. The performance that our method deals with occlusion and corruption problems is evaluated on different databases. In addition, we compare our method with state-the-of-art face recognition based methods, and the proposed method achieves the best results in face occlusion and disguise issues.

Keywords:face recognition, error detection, linear representation.

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