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This paper addresses the problem of 3D human action class and style class recognition as well as style transformations using Artificial Neural Networks. The training process is selected uniquely to suit the problem and a quantitative evaluation method is proposed for the results. Few other intelligent methods have also been applied for recognition and compared to our original approach. The results...
This paper proposes a 3D view-invariant human action recognition method based on Hidden Markov Models. The natures of the actions, as well as the characteristics of the actors and different performance styles have been successfully recognized. The results have been compared to nearest neighbor and similarity search based recognition for further evaluation. Also the research addresses the problem of...
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