Overlapping vehicle tracking via adaptive particle filter with multiple cues

W. L. Khong, W. Y. Kow, Y. K. Chin, I. Saad, K. T.K. Teo

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

4 Citations (Scopus)


Vehicle tracking is a vital approach to assist the on-road traffic surveillance system. Since the on-road vehicles is increasing, occlusion and overlapping of vehicles is often happen in the traffic surveillance scene. Therefore, segmentation and tracking of the occlusion or overlapped vehicle can be a challenging task in surveillance system via image processing. In this paper, a multiple cues overlapping vehicle tracking algorithm is proposed to continuously track the occluded vehicle effectively. The earlier vehicle tracking systems are normally based on colour feature which will leads to inaccurate results when the background colour is complex or too similar with the target vehicle. On the other hand, shape feature will increase the accuracy but consume more computation time in the resampling process during overlapping. The experimental results show that enhancement of the particle filter resampling process with multiple cues is capable to track the overlapped vehicle with higher accuracy and without compromising the processing time.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011
Number of pages6
Publication statusPublished - 2011
Externally publishedYes
EventIEEE International Conference on Control System, Computing and Engineering 2011 - Penang, Malaysia
Duration: 25 Nov 201127 Nov 2011
https://ieeexplore.ieee.org/xpl/conhome/6182936/proceeding (Proceedings)


ConferenceIEEE International Conference on Control System, Computing and Engineering 2011
Abbreviated titleICCSCE 2011
Internet address


  • likelihood
  • multiple cues
  • particle filter
  • vehicle tracking

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