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Proceedings Paper

Sparse presentation based classification with position-weighted block dictionary
Author(s): Jun He; Tian Zuo; Bo Sun; Xuewen Wu; Lejun Yu; Fengxiang Ge; Chao Chen
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Paper Abstract

This paper is aiming at applying sparse representation based classification (SRC) on general objects of a certain scale. Authors analyze the characteristics of general object recognition and propose a position-weighted block dictionary (PWBD) based on sparse presentation and design a framework of SRC with it (PWBD-SRC). Principle and implementation of PWBD-SRC have been introduced in the article, and experiments on car models have been given in the article. From experimental results, it can be seen that with position-weighted block dictionary (PWBD) not only the dictionary scale can be effectively reduced, but also roles of image blocks taking in representing a whole image can be embodied to a certain extent. In reorganization application, an image only containing partial objects can be identified with PWBD-SRC. Besides, rotation and perspective robustness can be achieved. Finally, a brief description on some remaining problems has been proposed in the article.

Paper Details

Date Published: 25 February 2014
PDF: 12 pages
Proc. SPIE 9019, Image Processing: Algorithms and Systems XII, 90190X (25 February 2014); doi: 10.1117/12.2039610
Show Author Affiliations
Jun He, Beijing Normal Univ. (China)
Tian Zuo, Beijing Normal Univ. (China)
Bo Sun, Beijing Normal Univ. (China)
Xuewen Wu, Beijing Normal Univ. (China)
Lejun Yu, Beijing Normal Univ. (China)
Fengxiang Ge, Beijing Normal Univ. (China)
Chao Chen, Naval Academy of Armament (China)

Published in SPIE Proceedings Vol. 9019:
Image Processing: Algorithms and Systems XII
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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