Dynamical Pose Filtering for Mixtures of Gaussian Processes
نویسندگان
چکیده
In this paper we present a method for performing discriminative human pose estimation using a mixture of Gaussian Processes appearance model to map directly from the image features to the multi-model pose distribution. In order to obtain a pose estimate for a sequence of frames, we introduce a dynamic programming algorithm for inferring a smooth pose sequence from the multi-model distribution given by our appearance model.
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