Abstract
Within this paper a technique for model-based 3D hand tracking is presented. A hand model is built from a set of truncated quadrics, approximating the anatomy of a real hand with few parameters. Given that the projection of a quadric onto the image plane is a conic, the contours can be generated efficiently. These model contours are used as shape templates to evaluate possible matches in the current frame. The evaluation is done within a hierarchical Bayesian filtering framework, where the posterior distribution is computed efficiently using a tree of templates. We demonstrate the effectiveness of the technique by using it for tracking 3D articulated and non-rigid hand motion from monocular video sequences in front of a cluttered background.
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Cipolla, R., Stenger, B., Thayananthan, A., Torr, P.H.S. (2005). Template-Based Hand Detection and Tracking. In: Tistarelli, M., Bigun, J., Grosso, E. (eds) Advanced Studies in Biometrics. Lecture Notes in Computer Science, vol 3161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11493648_7
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DOI: https://doi.org/10.1007/11493648_7
Publisher Name: Springer, Berlin, Heidelberg
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