A Two-phase Face Recognition Algorithm Based on Discriminative Low-rank Representation

doi:10.3969/j.issn.1006-2475.2019.12.011

Abstract

Abstract: A two-phase face recognition algorithm based on discriminative low-rank representation is proposed to deal with the noise in image training samples. In the first stage, all the training samples are processed by low-rank representation, and the M nearest neighbors of test sample are selected for rough classification. In the second stage, the samples screened in the first stage are used for discriminative low-rank representation, and sparse linear representation is used for fine classification, so as to determine the most suitable class labels for test samples. This algorithm combines the advantages of low-rank algorithm and sparse algorithm. The performance of this algorithm is proved by experiments on standard face database.

Key words: machine vision, face recognition, low-rank representation, transformation algorithm

CLC Number:

TP391

CUI Juan-juan1, ZHANG Lei1, HOU Xie-lian2, CHEN Cai-kou2, ZHANG Hai-yan1. A Two-phase Face Recognition Algorithm Based on Discriminative Low-rank Representation[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.12.011.

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