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Spatiotemporal vehicle tracking: the use of unsupervised learning-based segmentation and object tracking

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4 Author(s)
Shu-Ching Chen ; Sch. of Comput. Sci., Florida Int. Univ., Miami, FL, USA ; Mei-Ling Shyu ; Peeta, S. ; Chengcui Zhang

In this paper, a framework for spatiotemporal vehicle tracking using unsupervised learning-based segmentation and object tracking is presented. An adaptive background learning and subtraction method is proposed and applied to two real-traffic video sequences to obtain more accurate spatiotemporal information on the vehicle objects. As demonstrated in the experiments, almost all vehicle objects are successfully identified through this framework.

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Robotics & Automation Magazine, IEEE  (Volume:12 ,  Issue: 1 )