Real-Time Multi-view 3D Object Tracking in Cluttered Scenes

  • Huan Jin
  • Gang Qian
  • Stjepan Rajko
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4292)


This paper presents an approach to real-time 3D object tracking in cluttered scenes using multiple synchronized and calibrated cameras. The goal is to accurately track targets over a long period of time in the presence of complete occlusion in some of the camera views. In the proposed system, color histogram was used to represent object appearance. Tracked 3D object locations were smoothed and new locations predicted using a Kalman filter. The predicted object 3D location was then projected onto all camera views to provide a search region for robust 2D object tracking and occlusion detection. The experimental results were validated using ground-truth data obtained from a marker-based motion capture system. The results illustrate that the proposed approach is capable of effective and robust 3D tracking of multiple objects in cluttered scenes.


Color Histogram Camera View Search Region Color Segmentation Diamond Search 
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

  • Huan Jin
    • 1
    • 3
  • Gang Qian
    • 2
    • 3
  • Stjepan Rajko
    • 1
    • 3
  1. 1.Dept. of Computer Science and Engineering 
  2. 2.Dept. of Electrical Engineering 
  3. 3.Arts, Media and Engineering ProgramArizona State UniversityTempeUSA

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