Overlapping Vehicle Tracking via Adaptive Particle Filter with Multiple Cues

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dc.contributor.authorW.L. Khong
dc.contributor.authorW.Y. Kow
dc.contributor.authorY.K. Chin
dc.contributor.authorI. Saad
dc.contributor.authorK.T.K. Teo
dc.date.accessioned2023-06-06T07:52:32Z
dc.date.available2023-06-06T07:52:32Z
dc.date.issued2011
dc.descriptionModelling, Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu, Malaysia msclab@ums.edu.my, ktkteo@ieee.org Keywords - vehicle tracking; particle filter; likelihood; multiple cues
dc.description.abstractVehicle tracking is a vital approach to assist the onroad 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.
dc.identifier.urihttps://digitallibrary.peninsulacollege.edu.my/handle/123456789/339
dc.language.isoen
dc.titleOverlapping Vehicle Tracking via Adaptive Particle Filter with Multiple Cues
dc.typeArticle
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