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Global temporal registration of multiple non-rigid surface sequences

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3 Author(s)
Peng Huang ; Centre for Vision Speech Signal Processing, University of Surrey, University of Surrey, Guildford, UK, GU2 7XH ; Chris Budd ; Adrian Hilton

In this paper we consider the problem of aligning multiple non-rigid surface mesh sequences into a single temporally consistent representation of the shape and motion. A global alignment graph structure is introduced which uses shape similarity to identify frames for inter-sequence registration. Graph optimisation is performed to minimise the total non-rigid deformation required to register the input sequences into a common structure. The resulting global alignment ensures that all input sequences are resampled with a common mesh structure which preserves the shape and temporal correspondence. Results demonstrate temporally consistent representation of several public databases of mesh sequences for multiple people performing a variety of motions with loose clothing and hair.

Published in:

Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on

Date of Conference:

20-25 June 2011