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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Region-Level Motion-Based Foreground Detection with Shadow Removal Using MRFs
verfasst von : Shih-Shinh Huang, Li-Chen Fu, Pei-Yung Hsiao
Erschienen in: Computer Vision – ACCV 2006
Verlag: Springer Berlin Heidelberg
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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.