 A Collaborative Neighbor Representation Based Face Recognition AlgorithmZhengming Li, Qi Zhu, Binglei Xie, Jian Cao and Jin Zhang Mathematical Problems in Engineering, 2013, vol. 2013, 1-9 Abstract: We propose a new collaborative neighbor representation algorithm for face recognition based on a revised regularized reconstruction error (RRRE), called the two-phase collaborative neighbor representation algorithm (TCNR). Specifically, the RRRE is the division of   -norm of reconstruction error of each class into a linear combination of   -norm of reconstruction coefficients of each class, which can be used to increase the discrimination information for classification. The algorithm is as follows: in the first phase, the test sample is represented as a linear combination of all the training samples by incorporating the neighbor information into the objective function. In the second phase, we use the classes to represent the test sample and calculate the collaborative neighbor representation coefficients. TCNR not only can preserve locality and similarity information of sparse coding but also can eliminate the side effect on the classification decision of the class that is far from the test sample. Moreover, the rationale and alternative scheme of TCNR are given. The experimental results show that TCNR algorithm achieves better performance than seven previous algorithms. Date: 2013 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:373858 DOI: 10.1155/2013/373858 Access Statistics for this article More articles in Mathematical Problems in Engineering from Hindawi |
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