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Reyes M.,University of Barcelona | Reyes M.,Computer Vision Center Campus | Dominguez G.,University of Barcelona | Escalera S.,University of Barcelona | Escalera S.,Computer Vision Center Campus
Proceedings of the IEEE International Conference on Computer Vision | Year: 2011

We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach. © 2011 IEEE. Source

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