8 October 2015 Face recognition using multiple maximum scatter difference discrimination dictionary learning
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Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96750H (2015) https://doi.org/10.1117/12.2197395
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China
Abstract
Based on multiple maximum scatter difference discrimination Dictionary learning, a novel face recognition algorithm is proposed. Dictionary used for sparse coding plays a key role in sparse representation classification. In this paper, a multiple maximum scatter difference discriminated criterion is used for dictionary learning. During the process of dictionary learning, the multiple maximum scatter difference computes its discriminated vectors from both the range of the between class scatter matrix and the null space of the within-class scatter matrix. The proposed algorithm is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the AR database and Extended Yale Database B in comparison with existing basic sparse representation and other classification methods, it shows that the performance is a little better than the original sparse representation methods with lower complexity.
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Yanyong Zhu, Yanyong Zhu, Jiwen Dong, Jiwen Dong, Hengjian Li, Hengjian Li, } "Face recognition using multiple maximum scatter difference discrimination dictionary learning", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96750H (8 October 2015); doi: 10.1117/12.2197395; https://doi.org/10.1117/12.2197395
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