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Multivariate statistics / Cluster analysis / User interface techniques / Gesture recognition / Gesture / Segmentation / Hidden Markov model / Mixture model / K-means clustering / Statistics / Machine learning / Data analysis


Auto clustering for unsupervised learning of atomic gesture components using minimum description len - Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 2001. Proceedings.
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Document Date: 2010-08-11 10:30:20


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File Size: 1,18 MB

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Zurich / Corfu / Southampton / Yvette / Freiburg / /

Company

Wilson / Real-Time Systems / IEEE Comp / /

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Germany / France / United Kingdom / Greece / /

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Facility

Westfield College / University of Leeds / University of Chicago Press / University of Westminster / University of Westminster Department / University Westminster / University of Westminster Eprints / /

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unsupervised online learning / constructive algorithms / online adaptive gesture recognition / electromagnetic tracking device / k-means clustering algorithm / be determined using constructive algorithms / /

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U.K. / /

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University of Westminster Eprints / University of Chicago Press / Queen Mary and Westfield College / London / Harrow School of Computer Science / University of Westminster Department of Computer Science / University of Leeds / University of Westminster / /

Person

Alexandra Psarrou / Mary / /

Position

E. Hunter / and R. Jain / speaker / /

Technology

ASL / Clustering algorithms / k-means clustering algorithm / Gesture Recognition / EM algorithm / determined using a standard k-means clustering algorithm / /

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