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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 8 — Sep. 4, 2013

Dissimilarity sparsity-preserving projections in feature extraction for visual recognition

Fengtao Xiang, Zhengzhi Wang, and Xingsheng Yuan  »View Author Affiliations


Applied Optics, Vol. 52, Issue 20, pp. 5022-5029 (2013)
http://dx.doi.org/10.1364/AO.52.005022


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Abstract

This paper investigates the use of feature dimensionality reduction approaches for high-dimensional data analysis. Most of the existing preserving projection methods are based on similarity, such as the well-known locality-preserving projections, neighborhood-preserving embedding, and sparsity-preserving projections. Here, we propose a simple yet very efficient preserving projection method based on sparsity and dissimilarity for feature extraction, named dissimilarity sparsity-preserving projections, which is an extended version of sparsity-preserving projections. Both projection coefficients and reconstructive residuals are considered in our proposed framework. We give an idea of a “dissimilarity metric” as the measurement of the relationship among the object data. If the value of the dissimilarity metric of two samples is large, the possibility of them belonging to the same class is small. The proposed methods do not have to preset the number of neighbors and heat kernel width, which is one of the important differences from other projection methods. In practical applications, an approximately direct and complete solution is obtained for the proposed algorithm. Experimental results on three widely used face datasets demonstrate that the proposed framework could achieve competitive performance in terms of accuracy and efficiency.

© 2013 Optical Society of America

OCIS Codes
(070.5010) Fourier optics and signal processing : Pattern recognition
(100.0100) Image processing : Image processing
(100.2000) Image processing : Digital image processing
(100.5010) Image processing : Pattern recognition
(100.3008) Image processing : Image recognition, algorithms and filters

ToC Category:
Image Processing

History
Original Manuscript: March 18, 2013
Revised Manuscript: June 5, 2013
Manuscript Accepted: June 5, 2013
Published: July 10, 2013

Virtual Issues
Vol. 8, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Fengtao Xiang, Zhengzhi Wang, and Xingsheng Yuan, "Dissimilarity sparsity-preserving projections in feature extraction for visual recognition," Appl. Opt. 52, 5022-5029 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-52-20-5022

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