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|Title:||Smooth foreground-background segmentation for video processing|
|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|
|Series/Report no.:||Lecture Notes in Computer Science, 2006; 3851: 581-590|
|Conference Name:||Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India)|
|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|
|Appears in Collections:||Aurora harvest|
Computer Science publications
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