Non-parametric Background Generation based on MRF Framework


The KIPS Transactions:PartB , Vol. 17, No. 6, pp. 405-412, Dec. 2010
10.3745/KIPSTB.2010.17.6.405,   PDF Download:

Abstract

Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts, To overcome this problem. in this paper. we propose a new background generation method which incorporates spatial as well as temporal contexts of the image, This enabled us to obtain `clean` background image with no moving objects. In our proposed method. first we divided the Sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static. we used MRF framework to model them in temporal and spatial contexts, MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.


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Cite this article
[IEEE Style]
S. H. Cho and H. B. Kang, "Non-parametric Background Generation based on MRF Framework," The KIPS Transactions:PartB , vol. 17, no. 6, pp. 405-412, 2010. DOI: 10.3745/KIPSTB.2010.17.6.405.

[ACM Style]
Sang Hyun Cho and Hang Bong Kang. 2010. Non-parametric Background Generation based on MRF Framework. The KIPS Transactions:PartB , 17, 6, (2010), 405-412. DOI: 10.3745/KIPSTB.2010.17.6.405.