In this paper, we propose a coherent framework for joint key-frame extraction and object-based video segmentation. Conventional key-frame extraction and object segmentation are usually implemented independently and separately due to the fact that they are on different semantic levels. This ignores the inherent relationship between key-frames and objects. The proposed method extracts a small number of key-frames within a shot so that the divergence between video objects in a feature space can be maximized, supporting robust and efficient object segmentation. This method can utilize advantages of both temporal and object-based video segmentations, and be helpful to build a unified framework for content-based analysis and structured video representation. Theoretical analysis and simulation results on both synthetic and real video sequences manifest the efficiency and robustness of the proposed method.


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    Titel :

    Joint Key-Frame Extraction and Object-Based Video Segmentation


    Beteiligte:
    Song, Xiaomu (Autor:in) / Fan, Guoliang (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    329346 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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