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Communication Dans Un Congrès Année : 2016

Laban movement analysis for real-time 3D gesture recognition

Résumé

In this paper, we propose a new method for body gesture recognition based upon Laban Movement Analysis (LMA). The features are computed for a dataset of pre-segmented sequences putting at stake 11 different actions, and are used to build a dictionary of key poses, obtained with the help of a k-means clustering approach. A soft assignment method based upon the obtained poses is applied to the dataset and assignment results are used as input sequences in a Hidden Markov Models (HMM) framework for real-time action recognition purpose. The high recognition rates obtained (more than 92% for certain gestures), demonstrate the pertinence of the proposed method
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Dates et versions

hal-01451739 , version 1 (01-02-2017)

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  • HAL Id : hal-01451739 , version 1

Citer

Arthur Truong, Titus Zaharia. Laban movement analysis for real-time 3D gesture recognition. MEASURING BEHAVIOR 2016 : 10th International Conference on Methods and Techniques in Behavioral Research, May 2016, Dublin, Ireland. pp.514 - 521. ⟨hal-01451739⟩
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