Human body tracking by monocular vision

  • F. Lerasle
  • G. Rives
  • M. Dhome
  • A. Yassine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)


This article describes a tracking method of 3D articulated complex objects (for example, the human body), from a monocular sequence of perspective images. These objects and their associated articulations must be modelled. The principle of the method is based on the interpretation of image features as the 3D perspective projections points of the object model and an iterative Levenberg-Marquardt process to compute the model pose in accordance with the analysed image.

This attitude is filtered (Kalman filter) to predict the model pose relative to the following image of the sequence. The image features are extracted locally according to the computed prediction.

Tracking experiments, illustrated in this article by a cycling sequence, have been conducted to prove the validity of the approach.


monocular vision articulated polyhedric model matchings localization tracking 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • F. Lerasle
    • 1
  • G. Rives
    • 1
  • M. Dhome
    • 1
  • A. Yassine
    • 1
  1. 1.LAboratoire des Sciences et Matériaux pour l'Electronique, et d'Automatique URA 1793 of the CNRSUniversité Blaise-Pascal de Clermont-FerrandAubière CedexFrance

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