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Towards Probabilistic Shape Vision in RoboCup: A Practical Approach

  • Sven Olufs
  • Florian Adolf
  • Ronny Hartanto
  • Paul Plöger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4434)

Abstract

This paper presents a robust object tracking method using a sparse shape-based object model. Our approach consists of three ingredients namely shapes, a motion model and a sparse (non-binary) subsampling of colours in background and foreground parts based on the shape assumption. The tracking itself is inspired by the idea of having a short-term and a long-term memory. A lost object is ”missed” by the long-term memory when it is no longer recognized by the short-term memory. Moreover, the long-term memory allows to re-detect vanished objects and using their new position as a new initial position for object tracking. The short-term memory is implemented with a new Monte Carlo variant which provides a heuristic to cope with the loss-of-diversity problem. It enables simultaneous tracking of multiple (visually) identical objects. The long-term memory is implemented with a Bayesian Multiple Hypothesis filter. We demonstrate the robustness of our approach with respect to object occlusions and non-Gaussian/non-linear movements of the tracked object. We also show that tracking can be significantly improved by using compensating ego-motion. Our approach is very scalable since one can tune the parameters for a trade-off between precision and computational time.

Keywords

Monte Carlo Particle Filter Monte Carlo Variant Monte Carlo Localisation Probabilistic Data Association 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Sven Olufs
    • 1
  • Florian Adolf
    • 1
  • Ronny Hartanto
    • 1
  • Paul Plöger
    • 1
  1. 1.Department of Computer Science, Bonn-Rhein-Sieg University of Applied Sciences, D-53757 St. AugustinGermany

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