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ACCV
2010
Springer

Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition

9 years 11 months ago
Continuous Surface-Point Distributions for 3D Object Pose Estimation and Recognition
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instances in cluttered scenes. The object representation is a probabilistic expression of object parts through smooth surface-point distributions obtained by kernel density estimation on 3D point clouds. A multi-part, viewpoint-invariant model is learned incrementally from a set of roughly segmented, unregistered views, by sequentially registering and fusing the views with the incremental model. Registration is conducted by nonparametric inference of maximum-likelihood model parameters, using Metropolis
Renaud Detry, Justus H. Piater
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2010
Where ACCV
Authors Renaud Detry, Justus H. Piater
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