Smooth foreground-background segmentation for video processing
Date
2006
Authors
Schindler, K.
Wang, H.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
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
Statement of Responsibility
Konrad Schindler and Hanzi Wang
Conference Name
Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India)
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.
School/Discipline
Dissertation Note
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Description
© Springer-Verlag Berlin Heidelberg 2006