Global temporal registration of multiple non-rigid surface sequences

  • Authors:
  • Peng Huang;C. Budd;A. Hilton

  • Affiliations:
  • Centre for Vision Speech Signal Process., Univ. of Surrey, Guildford, UK;Centre for Vision Speech Signal Process., Univ. of Surrey, Guildford, UK;Centre for Vision Speech Signal Process., Univ. of Surrey, Guildford, UK

  • Venue:
  • CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
  • Year:
  • 2011

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Abstract

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.