Michael Betser

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In this paper, we present an approach for speaker diarization based on segmentation followed by bottom-up clustering, where clusters are modeled using adapted Gaussian mixture models. We propose a novel inter-cluster distance in the model parameter space which is easily computable and which can both be used as the dissimilarity measure in the clustering(More)
— We propose a context-based model of video abstraction exploiting both audio and video features and applied to tennis TV programs. We can automatically produce different types of summary of a given video depending on the users' constraints or preferences. We have first designed an efficient and accurate temporal segmentation of the video into segments(More)
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