https://scholars.lib.ntu.edu.tw/handle/123456789/117630
標題: | Efficient hierarchical method for background subtraction | 作者: | Chen, Yu-Ting CHU-SONG CHEN YI-PING HUNG Huang C.-R |
關鍵字: | Background subtraction; Contrast histogram; Hierarchical background modeling; Non-stationary background; Object detection; Video surveillance | 公開日期: | 2007 | 卷: | 40 | 期: | 10 | 起(迄)頁: | 2706-2715 | 來源出版物: | Pattern Recognition | 摘要: | Detecting moving objects by using an adaptive background 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. © 2006 Pattern Recognition Society. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/154590 https://www.scopus.com/inward/record.uri?eid=2-s2.0-34249105516&doi=10.1016%2fj.patcog.2006.11.023&partnerID=40&md5=6e10ba832b3413c37835df59b368bd19 |
ISSN: | 00313203 | DOI: | 10.1016/j.patcog.2006.11.023 | SDG/關鍵字: | Block codes; Mathematical models; Object recognition; Pixels; Tracking (position); Background subtraction; Contrast histograms; Hierarchical background modeling; Non-stationary background; Object detection; Video surveillance; Hierarchical systems |
顯示於: | 資訊工程學系 |
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