(Enter summary)
Abstract: ÐA new method for the representation, recognition, and interpretation of parameterized gesture is presented. By
parameterized gesture we mean gestures that exhibit a systematic spatial variation; one example is a point gesture where the relevant
parameter is the two-dimensional direction. Our approach is to extend the standard hidden Markov model method of gesture
recognition by including a global parametric variation in the output probabilities of the HMM states. Using a linear model of... (Update)
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BibTeX entry: (Update)
A. Wilson and A. Bobick. Parametric hidden markov models for gesture recognition. IEEE Trans. Pattern Analysis and Machine Intelligence, 21(9), 1999. http://citeseer.ist.psu.edu/wilson99parametric.html More
@article{ wilson99parametric,
author = "Andrew D. Wilson and Aaron F. Bobick",
title = "Parametric Hidden Markov Models for Gesture Recognition",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
volume = "21",
number = "9",
pages = "884-900",
year = "1999",
url = "citeseer.ist.psu.edu/wilson99parametric.html" }
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