Efficient hierarchical method for background subtraction

PATTERN RECOGNITION

卷:40

Article

Chen, Yu-Ting ; Chen, Chu-Song ; Huang, Chun-Rong ; Hung, Yi-Ping

关键词: hierarchical background modeling;    background subtraction;    contrast histogram;    non-stationary backgrounds object detection;    video surveillance;   

DOI  :  10.1016/j.patcog.2006.11.023

来源: Elsevier

【 摘 要 】

Detecting moving objects by using an adaptive back-round model is a critical component for many vision-based applications. Most background models were maintained in pixel-based forms, while some approaches began to study block-based representations which are more robust to non-stationary backgrounds. In this paper, we propose a method that combines pixel-based and block-based approaches into a single framework. We show that efficient hierarchical backgrounds can be built by considering that these two approaches are complementary to each other. In addition, a novel descriptor is proposed for block-based background modeling in the coarse level of the hierarchy. Quantitative evaluations show that the proposed hierarchical method can provide better results than existing single-level approaches. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

【 授权许可】

Free