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)
BACKGROUND Accumulating evidence suggests that many ovarian high-grade serous carcinomas (HGSCs) originate in the fallopian tube. Malignant cells shed by tubal lesions can be detected by examination of cytological samples from the endometrial cavity (endometrial cytological testing). To evaluate the use of this method for detecting HGSC, we examined(More)
In our past work on sports highlights extraction, we have shown the utility of detecting audience reaction using an audio classification framework. The audio classes in the framework were chosen based on intuition. In this paper, we present a systematic way of identifying the key audio classes for sports highlights extraciton using a time series clustering(More)
We have extended our sports video browsing framework for personal video recorders, such as recordable-DVD recorders, blu-ray disc recorders and/or hard disc recorders, to music segment detection. Our extension to Japanese broadcast music video programs consists of detecting audio segment boundaries such as conversations with guests followed by music/song(More)