We present a novel dataglove mapping technique based on parameterisable models that handle both the cross coupled sensors of the fingers and thumb, and the under-specified abduction sensors for the fingers. Our focus is on realistically reproducing the posture of the hand as a whole, rather than on accurate fingertip positions. The method proposed in this paper is a vision-free, object free, data glove mapping and calibration method that has been successfully used in robot manipulation tasks. © 2011 Springer-Verlag.
CITATION STYLE
Steffen, J., Maycock, J., & Ritter, H. (2011). Robust dataglove mapping for recording human hand postures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7102 LNAI, pp. 34–45). https://doi.org/10.1007/978-3-642-25489-5_4
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