Region-Level motion-based foreground detection with shadow removal using MRFs

Authors:
Shih-Shinh Huang;Li-Chen Fu;Pei-Yung Hsiao
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, R.O.C.;Department of Electronics Engineering, Chang Gung University, Tao-Yuan, Taiwan, R.O.C.
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

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Abstract

This paper presents a new approach to automatic segmentation of foreground objects with shadow removal from an image sequence by integrating techniques of background subtraction and motion-based foreground segmentation. First, a region-based motion segmentation algorithm is proposed to obtain a set of motion-coherence regions and the correspondence among regions at different time instants. Next, we formulate the foreground detection problem as a graph labeling over a region adjacency graph (RAG) based on Markov random fields (MRFs) statistical framework. A background model representing the background scene is built and then is used to model a likelihood energy. Besides the background model, the temporal and spatial coherence are also maintained by modeling it as a prior energy. Finally, a labeling is obtained by maximizing a posterior energy of the MRFs. Experimental results for several video sequences are provided to demonstrate the effectiveness of the proposed approach.