Similarity K-d tree method for sparse point pattern matching with underlying non-rigidity

We propose a method for matching non-affinely related sparse model and data point-sets of identical cardinality, similar spatial distribution and orientation. To establish a one-to-one match, we introduce a new similarity K-dimensional tree. We construct the tree for the model set using spatial spar...

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Bibliographic Details

Main Authors:	Baihua Li, Qinggang Meng, Horst Holstein
Format:	Default Article
Published:	2005
Subjects:	Artificial intelligence not elsewhere classified Other information and computing sciences not elsewhere classified Dimensional tree Non-rigid point pattern matching Non-rigid pose estimation Robust point pattern correspondence Motion capture Artificial Intelligence and Image Processing Information and Computing Sciences not elsewhere classified
Online Access:	https://hdl.handle.net/2134/20267
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