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Bootstrapping Sequential Monte Carlo Tracking

  • Thomas B. Moeslund
  • Erik Granum
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

Sequential Monte Carlo (SMC) methods have in recent years been applied to handle some of the problems inherent to model-based tracking. In this paper we suggest to apply bootstrapping to reduce the required number of particles in SMC tracking. By bootstrapping is meant to track reliable low-level image features and use them to bootstrap the high-level model-based tracking. The concept of bootstrapped SMC tracking is exemplified by monocular tracking of the 3D pose of a human arm with the position of the hand in the image as the bootstrapping information. Tests suggest that both bootstrapping is a sound strategies and an improvement over standard SMC-methods.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Thomas B. Moeslund
    • 1
  • Erik Granum
    • 1
  1. 1.Laboratory of Computer Vision and Media TechnologyAalborg UniversityDenmark

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