Shuji Zhao

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This paper presents an actor video retrieval system based on face video-tubes extraction and representation with sets of temporally coherent features. Visual features, SIFT points, are tracked along a video shot, resulting in sets of feature point chains (spatio-temporal tubes). These tubes are then classified and retrieved using a kernel-based SVM learning(More)
In the domain of multimedia, rapid DVD browsing or multi-media oriented web search require an efficient content-based image and video retrieval system. In this paper, we present our retrieval system of actors in films combining powerful machine learning techniques with " kernels on bags of bags " design. From a film segmented into shots, we extract(More)
In this article, we propose a new video object retrieval system. Our approach is based on a Spatio-Temporal data representation, a dedicated kernel design and a statistical learning toolbox for video object recognition and retrieval. Using state-of-the-art video object detection algorithms (for faces or cars, for example) we segment video object tracks from(More)
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