Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/56254
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Type: Conference paper
Title: Smooth foreground-background segmentation for video processing
Author: Schindler, K.
Wang, H.
Citation: Computer Vision – ACCV 2006: 7th Asian Conference on Computer Vision Hyderabad, India, January 13-16, 2006, Proceedings, Part II / P.J. Narayanan, Shree K. Nayar, Heung-Yeung Shum (eds.), pp.581-590
Publisher: Springer
Publisher Place: Berlin
Issue Date: 2006
Series/Report no.: Lecture Notes in Computer Science, 2006; 3851: 581-590
ISBN: 3540312196
ISSN: 0302-9743
1611-3349
Conference Name: Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India)
Statement of
Responsibility: 
Konrad Schindler and Hanzi Wang
Abstract: We propose an efficient way to account for spatial smoothness in foreground-background segmentation of video sequences. Most statistical background modeling techniques regard the pixels in an image as independent and disregard the fundamental concept of smoothness. In contrast, we model smoothness of the foreground and background with a Markov random field, in such a way that it can be globally optimized at video frame rate. As a background model, the mixture-of-Gaussian (MOG) model is adopted and enhanced with several improvements developed for other background models. Experimental results show that the MOG model is still competitive, and that segmentation with the smoothness prior outperforms other methods.
Description: © Springer-Verlag Berlin Heidelberg 2006
DOI: 10.1007/11612704_58
Appears in Collections:Aurora harvest
Computer Science publications

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