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A0221
Title: Stochastic shape analysis and probabilistic geometric statistics Authors:  Stefan Sommer - University of Copenhagen (Denmark) [presenting]
Abstract: Analysis and statistics of shape variation can be formulated in geometric settings with geodesics modelling transitions between shapes. Extensions of these smooth geodesic models will be considered to account for noise and uncertainty: Stochastic shape processes and stochastic shape matching algorithms. In the stochastic setting, matching algorithms take the form of bridge simulation schemes which also provide approximations of the transition density of the stochastic shape processes. Examples of stochastic shape processes and connected bridge simulation algorithms will be covered. We will connect these ideas to statistics for data on general manifolds, particularly to the diffusion mean.