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.


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    Titel :

    Region-Level Motion-Based Foreground Detection with Shadow Removal Using MRFs


    Beteiligte:
    Huang, Shih-Shinh (Autor:in) / Fu, Li-Chen (Autor:in) / Hsiao, Pei-Yung (Autor:in)


    Erscheinungsdatum :

    2006-01-01


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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