Yusuke Kamishima

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The aim of this section is to develop a high-performance semantic indexing system using Gaussian mixture model (GMM) supervectors and tree-structured GMMs [1, 2]. GMM spervectors corresponding to six types of audio and visual features are extracted from video shots by using tree-structured GMMs. The computational cost of maximum a posteriori (MAP)(More)
1 Overview In this paper, we present our systems for semantic indexing and surveillance event detection in TRECVID 2010. We propose a statistical framework for semantic indexing using Gaussian mixture model (GMM) supervector kernels with visual and audio features. For classifier we used a Maximal Figure-of-Merit (MFoM) classifier and support vector machines(More)
In large-scale multimedia event detection, complex target events are extracted from a large set of consumer-generated web videos taken in unconstrained environments. We devised a multimedia event detection method based on Gaussian mixture model (GMM) supervectors and support vector machines. A GMM supervector consists of the parameters of a GMM for the(More)
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