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This paper proposes a semantic audiovisual analysis approach for video summarization. The sequence to be analyzed is first segmented into scenes according to audio similarity. Some global clues such as loudness, the ratio of unrelated shots, and the affective relationship between the scenes and the whole sequence are employed to compute the semantic scene importance. The shots in each scene are grouped...
A novel shape descriptor, which can be extracted from the major object edges automatically and used for the multimedia content-based retrieval in multimedia databases, is presented. By adopting a multiscale approach over the edge field where the scale represents the amount of simplification, the most relevant edge segments, referred to as subsegments, which eventually represent the major object boundaries,...
A scene segmentation method utilizing both visual features and motion features of video is presented in this paper. Not only the visual similarity but also the motion consistency of shots within a scene is considered in clustering shots into scenes. In addition, a method to merge the over-segmented scenes is presented also. And the experimental results show the effectiveness of the proposed algorithms.
This paper describes a three-pass segmentation algorithm followed by a foreground/background extraction rule. Being imperfect, the basic objective of the proposed segmentation is to enable the extraction of objects that may be of main interest to the user, and the background. The formed segments are assigned points, according to the location of their center of mass and bounding box coordinates, and...
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