Abstract
We present a method for recognizing gesture motions based on elastic deformable shapes and curvature templates. Gestures are modeled using a spline curve representation that is enhanced with elastic properties: the entire spline or any of its parts may stretch or bend. The energy required to transform a gesture into a given template gives an estimation of the similarity between the two. We demonstrate the results of our gesture classifier with a video-based acquisition approach.
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Vatavu, RD., Grisoni, L., Pentiuc, SG. (2009). Gesture Recognition Based on Elastic Deformation Energies. In: Sales Dias, M., Gibet, S., Wanderley, M.M., Bastos, R. (eds) Gesture-Based Human-Computer Interaction and Simulation. GW 2007. Lecture Notes in Computer Science(), vol 5085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92865-2_1
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DOI: https://doi.org/10.1007/978-3-540-92865-2_1
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