Dynamic tracking system through PSO and Parzen particle filter

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Abstract

Transportation plays a pivotal role in our society, especially in a good quality of life and economic prosperity. Intelligent transportation system (ITS) has been developed to manage the transport infrastructure and vehicles since the number of vehicles is rapidly growing and to avoid any accident. Various applications have provided to support ITS. One of them is a driver-assistant system. Considering of heavy vehicles such as bus, truck, trailer and etc., the driver assistant system is of importance in monitoring and recognizing objects in vehicle surrounding. For example, in operating a heavy vehicle, a driver has a limited view of the vehicle surrounding itself. It is difficult for the driver to ensure that the surrounding of vehicle is safe before operating the machine. Thus, in this paper, we employ a video tracking system through PSO and Parzen particle filter to break through several problems such as simultaneous motion and occlusion among objects. This method makes it easy to track a human movement from every frame and indirectly require less a processing time for tracking an object location in a video stream compared to conventional method. The detail outcome and result are discussed using experiments of the method in this paper. © 2009 Springer Berlin Heidelberg.

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APA

Musa, Z. B., Watada, J., Yan, S., & Ding, H. (2009). Dynamic tracking system through PSO and Parzen particle filter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5712 LNAI, pp. 220–227). https://doi.org/10.1007/978-3-642-04592-9_28

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