publication . Conference object . 2008

Learning stick-figure models using nonparametric Bayesian priors over trees

Edward W. Meeds; David A. Ross; Richard S. Zemel; Sam T. Roweis;
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  • Published: 12 Aug 2008
  • Publisher: IEEE
Abstract
We present a probabilistic stick-figure model that uses a nonparametric Bayesian distribution over trees for its structure prior. Sticks are represented by nodes in a tree in such a way that their parameter distributions are probabilistically centered around their parent node. This prior enables the inference procedures to learn multiple explanations for motion-capture data, each of which could be trees of different depth and path lengths. Thus, the algorithm can automatically determine a reasonable distribution over the number of sticks in a given dataset and their hierarchical relationships. We provide experimental results on several motion-capture datasets, d...
Subjects
ACM Computing Classification System: ComputingMethodologies_COMPUTERGRAPHICS
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