Abstract
In this paper, we present GREFIT (Gesture REcognition based on FInger Tips) which is able to extract the 3-dimensional hand posture from video images of the human hand. GREFIT uses a two-stage approach to solve this problem.
This paper is based on earlier presented results of a system to locate the 2-D positions of the fingertips in images. We now describe the second stage, where the 2-D position information is transformed by an artificial neural net into an estimate of the 3-D configuration of an articulated hand model, which is also used for visualization. This model is designed according to the dimensions and movement possibilities of a natural human hand.
The virtual hand imitates the user’s hand to an astonishing accuracy and can track postures from grey scale images at a speed of 10 Hz.
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© 1999 Springer-Verlag Berlin Heidelberg
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Nölker, C., Ritter, H. (1999). GREFIT: Visual Recognition of Hand Postures. In: Braffort, A., Gherbi, R., Gibet, S., Teil, D., Richardson, J. (eds) Gesture-Based Communication in Human-Computer Interaction. GW 1999. Lecture Notes in Computer Science(), vol 1739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46616-9_6
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DOI: https://doi.org/10.1007/3-540-46616-9_6
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