Abstract: Video clip is the dominant component of multimedia system. However, video data are voluminous. An effective and efficient visual data management system is highly desired. Recent technology in digital video processing has moved to 'content-based' storage and retrieval. To detect meaningful area/region, using only production and camera operation- based detection is not enough. The contents of a video also have to be considered. The basic idea of this scheme is that if we can distinguish individual objects in the whole video sequence, we would be able to capture the changes in content throughout the sequences. Among many object features, motion content has been widely used as an important key in video storage and retrieval systems. Therefore, through motion- based representation, this paper will investigate an algorithm for sub-shot extraction and key-frame selection. From a given video sequence, first we segment the sequence into shots by using some of the production and camera operation-based detection techniques. Then, from the beginning of each shot, we calculate optical flow vectors by using complex wavelet phase-matching-based method on a pair of successive frames. Next, we segment each moving object based on these vectors using clustering in a competitive agglomeration scheme and represent them into a number of layers. After separating moving object(s) from each other for every frame in this shot, we extract sub-shots and select key-frames by using information about the presence and absence of moving object in each layer. Finally, these key-frames and sub-shots have been used to represent the whole video in panoramic mosaic-based representation form. Experimental results showing the significance of the proposed method are also provided. !20
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