Global Non-rigid Alignment of Surface Sequences
Budd, C, Huang, P, Klaudiny, M and Hilton, A (2012) Global Non-rigid Alignment of Surface Sequences International Journal of Computer Vision.
Available under License : See the attached licence file.
This paper presents a general approach based on the shape similarity tree for non-sequential alignment across databases of multiple unstructured mesh sequences from non-rigid surface capture. The optimal shape similarity tree for non-rigid alignment is defined as the minimum spanning tree in shape similarity space. Non-sequential alignment based on the shape similarity tree minimises the total non-rigid deformation required to register all frames in a database into a consistent mesh structure with surfaces in correspondence. This allows alignment across multiple sequences of different motions, reduces drift in sequential alignment and is robust to rapid non-rigid motion. Evaluation is performed on three benchmark databases of 3D mesh sequences with a variety of complex human and cloth motion. Comparison with sequential alignment demonstrates reduced errors due to drift and improved robustness to large non-rigid deformation, together with global alignment across multiple sequences which is not possible with previous sequential approaches. © 2012 The Author(s).
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Date :||August 2012|
|Identification Number :||https://doi.org/10.1007/s11263-012-0553-4|
|Related URLs :|
|Additional Information :||The original publication is available at http://www.springerlink.com/index/10.1007/s11263-012-0553-4|
|Depositing User :||Symplectic Elements|
|Date Deposited :||11 Feb 2013 15:10|
|Last Modified :||23 Sep 2013 20:00|
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