Laplacian-Uniform Mixture-Driven Iterative Robust Coding With Applications to Face Recognition Against Dense Errors

Outliers due to occlusion, pixel corruption, and so on pose serious challenges to face recognition despite the recent progress brought by sparse representation. In this article, we show that robust statistics implemented by the state-of-the-art methods are insufficient for robustness against dense g...

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Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 31; no. 9; pp. 3620 - 3633
Main Authors:	Zheng, Huicheng, Lin, Dajun, Lian, Lina, Dong, Jiayu, Zhang, Peipei
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.09.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Approximation algorithms Coding Coding residual Corruption Encoding Error correction Error correction & detection Error detection Face Face recognition Facial recognition technology Iterative methods Minimization non-convexity Objective function Occlusion outlier Outliers (statistics) Pattern recognition Representations Robustness sparse representation Training
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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