Study of recognizing human motion observed from an arbitrary viewpoint based on decomposition of a tensor containing multiple view motions

Takayuki Hori*, Jun Ohya, Jun Kurumisawa

*Corresponding author for this work

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


We propose a Tensor Decomposition based algorithm that recognizes the observed action performed by an unknown person and unknown viewpoint not included in the database. Our previous research aimed motion recognition from one single viewpoint. In this paper, we extend our approach for human motion recognition from an arbitrary viewpoint. To achieve this issue, we set tensor database which are multi-dimensional vectors with dimensions corresponding to human models, viewpoint angles, and action classes. The value of a tensor for a given combination of human silhouette model, viewpoint angle, and action class is the series of mesh feature vectors calculated each frame sequence. To recognize human motion, the actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for each combination of action, person, and viewpoint. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. The recognition results show the validity of our proposed method, the method is experimentally compared with Nearest Neighbor rule. Our proposed method is very stable as each action was recognized with over 75% accuracy.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging IX
Publication statusPublished - 2011 Mar 29
EventComputational Imaging IX - San Francisco, CA, United States
Duration: 2011 Jan 242011 Jan 25

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceComputational Imaging IX
Country/TerritoryUnited States
CitySan Francisco, CA


  • Computer vision
  • Core tensor
  • Human motion analysis
  • Human motion recognition
  • Motion signature
  • Multiple viewpoint
  • N-mode SVD
  • Tensor decomposition

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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