Human motion tracking using nonsynchronous multiple observations

Hiroki Mori*, Akira Utsumi, Jun Ohya, Masahiko Yachida, Ryohei Nakatsu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This paper proposes a method of tracking a human object by using nonsynchronous multiple-viewpoint images. The proposed method tracks human forms efficiently by using a Kalman filter to integrate observed information which is obtained nonsynchronously from multiple viewpoints. The experimental system is composed of multiple observation nodes, which operate nonsynchronously to process the multiviewpoint images, a tracking node, which tracks the human figure, and the discovering node, which finds the human figure. The image features are matched to the tracking model in the observation node based on the prediction of the observed value which is sent from the tracking node. The image features matched to the model are sent to the tracking node, and the tracking model is updated. The image features which are not matched are sent to the discovering node to find a new human figure. With the proposed approach, it is possible to construct a large-scale tracking system while reducing the deterioration of processing efficiency and the redundancy among observations that occur in synchronous systems. The effectiveness of the proposed method is demonstrated by an experiment using real images.

Original languageEnglish
Pages (from-to)84-93
Number of pages10
JournalElectronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
Issue number12
Publication statusPublished - 2004 Dec


  • Distributed processing
  • Human tracking
  • Kalman filter
  • Multiple cameras
  • Nonsynchronous multiviewpoint image

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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