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Robust Vehicle Tracking Multi-feature Particle Filter

  • M. Eren Yildirim
  • Jongkwan Song
  • Jangsik Park
  • Byung Woo Yoon
  • Yunsik Yu
Part of the Communications in Computer and Information Science book series (CCIS, volume 263)

Abstract

Object detection and tracking have been studied separately in most cases. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. This paper presents a new method for tracking moving vehicles with temporal disappearance. The proposed method can continue tracking after disappearance. Color distribution of objects is integrated into particle filtering algorithm. As the color of an object can vary over time dependent on the illumination, a likelihood model is used including color cue and detection cue. Color cue is provided by using Bhattacharyya distance, and detection cue is provided by Euclidean distance. Tests are made by using highway cameras that are located on bridge.

Keywords

Particle filtering Color distribution Euclidean distance Bhattacharyya distance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • M. Eren Yildirim
    • 1
  • Jongkwan Song
    • 1
  • Jangsik Park
    • 1
  • Byung Woo Yoon
    • 1
  • Yunsik Yu
    • 2
  1. 1.Department of Electronics EngineeringKyungsung UniversityBusanKorea
  2. 2.Convergence of IT Devices Institute BusanBusanKorea

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