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Robust Appearance Modeling for Pedestrian and Vehicle Tracking

  • Wael Abd-Almageed
  • Larry S. Davis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4122)

Abstract

This paper describes a system for tracking people and vehicles for stationary-camera visual surveillance. The appearance of objects being tracked is modeled using mixtures of mixtures of Gaussians. Particles filters are used to track the states of object. Results show the robustness of the system to various lighting and object conditions.

Keywords

Particle Filter Object Tracking Appearance Model Vehicle Tracking Tracking People 
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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References

  1. 1.
    Abd-Almageed, W., Davis, L.S.: Density Estimation using Mixture of Mixtures of Gaussians. In: 9th European Conference on Computer Vision (2006)Google Scholar
  2. 2.
    Comaniciu, D., Meer, P.: Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Trans. Pattern Analysis and Machine Intelligence 24 (2002)Google Scholar
  3. 3.
    Han, H., Comaniciu, D., Zhu, Y., Davis, L.: Incremental Density Approximation and Kernel-Based Baesian Filtering for Object Tracking. In: IEEE International Conference on Computer Vision and Pattern Recognition, IEEE Computer Society Press, Los Alamitos (2004)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Wael Abd-Almageed
    • 1
  • Larry S. Davis
    • 1
  1. 1.Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742 

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