Stochastic Prediction of Waypoints for Extended Range Telepresence Applications
نویسندگان
چکیده
The Motion Compression framework for extended range telepresence applications consists of three functional modules: path prediction, path transformation, and user guidance. This paper presents a new path prediction module for known environments that exploits the property, that humans typically walk on straight paths toward discrete goal objects. In order to estimate the user’s goal object out of a set of possible goals, we derived a Bayesian filter that gives this discrete estimate based on continuous measurements of the user’s head pose.
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