Robot Position Estimation and Tracking Using the Particle Filter and SOM in Robotic Space

  • TaeSeok Jin
  • JangMyung Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4282)


The Robotic Space is the space where many intelligent sensing and tracking devices, such as computers and multi sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in Robotic Space, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into SOM based particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-motion tracking. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.


Mobile Robot Particle Filter Appearance Model Trajectory Prediction Intelligent Device 
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 2006

Authors and Affiliations

  • TaeSeok Jin
    • 1
  • JangMyung Lee
    • 2
  1. 1.Dept. of Mechatronics EngineeringDongSeo UniversityBusanKorea
  2. 2.Dept. of Elctronics EngineeringPusan National UniversityBusanKorea

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