Abstract
This paper presents a new approach to real-time scale and rotation invariant hand pose detection, which is based on a technique for computing the best hand skin color segmentation map. This segmentation map, a vector entity referred to as a “skin profile”, is used during an online hand gesture calibration stage to enable correct classification of skin regions. Subsequently, we construct efficient and reliable scale and rotation invariant hand pose gesture descriptors, by introducing an innovative technique, referred to as “oriented gesture descriptors”. Finally, hand pose gesture recognition is computed using a template matching technique which is luminance invariant.
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Bastos, R., Sales Dias, M. (2009). Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition. 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_8
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DOI: https://doi.org/10.1007/978-3-540-92865-2_8
Publisher Name: Springer, Berlin, Heidelberg
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