Isao Otsuka

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We present a novel genre-independent SVM framework for detecting scene changes in broadcast video. Our framework works on content from a diverse range of genres by allowing sets of features , extracted from both audio and video streams, to be combined and compared automatically without the use of explicit thresholds. For ground truth, we use hand-labeled(More)
We present a novel video summarization and skimming technique using face detection on broadcast video programs. We take the faces in video as our primary target as they constitute the focus of most consumer video programs. We detect face tracks in video and define face-scene fragments based on start and end of face tracks. We define a fast-forward skimming(More)
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