Quantifying the effect of a colored glove in the 3d tracking of a human hand

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Abstract

Research in vision-based 3D hand tracking targets primarily the scenario in which a bare hand performs unconstrained motion in front of a camera system. Nevertheless, in several important application domains, augmenting the hand with color information so as to facilitate the tracking process constitutes an acceptable alternative. With this observation in mind, in this work we propose a modification of a state of the art method [12] for markerless 3D hand tracking, that takes advantage of the richer observations resulting from a colored glove. We do so by modifying the 3D hand model employed in the aforementioned hypothesize-and-test method as well as the objective function that is minimized in its optimization step. Quantitative and qualitative results obtained from a comparative evaluation of the baseline method to the proposed approach confirm that the latter achieves a remarkable increase in tracking accuracy and robustness and, at the same time, reduces drastically the associated computational costs.

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Roditakis, K., & Argyros, A. A. (2015). Quantifying the effect of a colored glove in the 3d tracking of a human hand. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9163, pp. 404–414). Springer Verlag. https://doi.org/10.1007/978-3-319-20904-3_36

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