Visualising and Clustering Video Data
We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) . But whereas the GTM is an extension of a mixture of experts, this model is an extension of a product of experts . We show visualisation and clustering results on a data set composed of video data of lips uttering 5 Korean vowels and show that the new mapping achieves better results than the standard Self-Organizing Map.
KeywordsLatent Point Video Data English Word Data Space Visual Data
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