Mixture of Probabilistic Principal Component Analyzers for Shapes from Point Sets.

IEEE Transactions on Pattern Analysis and Machine Intelligence(2018)

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摘要
Inferring a probability density function (pdf) for shape from a population of point sets is a challenging problem. The lack of point-to-point correspondences and the non-linearity of the shape spaces undermine the linear models. Methods based on manifolds model the shape variations naturally, however, statistics are often limited to a single geodesic mean and an arbitrary number of variation modes...
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关键词
Shape,Principal component analysis,Sociology,Manifolds,Data models,Probability density function
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