Improvement of pose imitation method: A signal processing perspective

Tiezheng Mao, Aihua Mao, Osamu Yoshie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Pose imitation is for two shapes to study pose from each other. It has been a hot area in shape deformation and we improve the original graphical pose imitation method by introducing signal thought. Laplace framework is often used in pose imitation and geometrical information involved Laplace operator performs better in preserving original shape's mass smooth part by carrying much intrinsic information of graph. However, the two shapes' bases in Laplace feature space need to be well mapped before utilizing classical pose imitation algorithm, which makes it an obstacle to introduce the geometry related Laplace operator. In our work, the problem is solved by proposing signal transfer algorithm and based on it, we put out an effective pose imitation framework using edge length related Laplace operator. Our method well suits to 2-dimension shape and good results of pose imitation have been achieved.

Original languageEnglish
Title of host publicationEighth International Conference on Digital Image Processing, ICDIP 2016
PublisherSPIE
Volume10033
ISBN (Electronic)9781510605039
DOIs
Publication statusPublished - 2016
Event8th International Conference on Digital Image Processing, ICDIP 2016 - Chengu, China
Duration: 2016 May 202016 May 23

Other

Other8th International Conference on Digital Image Processing, ICDIP 2016
CountryChina
CityChengu
Period16/5/2016/5/23

Keywords

  • Laplace operator
  • Pose imitation
  • Signal transfer
  • Spectral analysis.

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Mao, T., Mao, A., & Yoshie, O. (2016). Improvement of pose imitation method: A signal processing perspective. In Eighth International Conference on Digital Image Processing, ICDIP 2016 (Vol. 10033). [100335C] SPIE. https://doi.org/10.1117/12.2244949