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Proceedings Paper

A basis-background subtraction method using non-negative matrix factorization
Author(s): Yaqi Chu; Xiaotian Wu; Tong Liu; Jun Liu
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Paper Abstract

In this paper, we proposed a basis-background subtraction method using non-negative matrix factorization (NMF). The core idea is to learn the parts of complex background environments by NMF algorithm and exploit the discrimination information in the training set to boost the reconstruction capability of the background efficiently. The method utilize the distance between an observed image and the reconstructed background image for segmenting foreground objects. The principle component analysis (PCA) is used for the enhanced initialization of NMF algorithm. A kind of off-line basis-background maintenance scheme is introduced instead of an incremental learning. A variety of experiments are conducted and illustrate the effectiveness in background subtraction. Quantitative evaluation and comparison with the existing methods show that the proposed method provides good improved results.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75461A (26 February 2010); doi: 10.1117/12.853445
Show Author Affiliations
Yaqi Chu, Sun Yat-Sen Univ. (China)
Xiaotian Wu, Sun Yat-Sen Univ. (China)
Tong Liu, Sun Yat-Sen Univ. (China)
Jun Liu, Sun Yat-Sen Univ. (China)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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