TY - GEN
T1 - Dynamic tracking system through PSO and Parzen particle filter
AU - Musa, Zalili Binti
AU - Watada, Junzo
AU - Yan, Sun
AU - Ding, Haochen
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Dynamic tracking system
KW - Human tracking
KW - Parzen particle filter
KW - PSO
KW - Template matching
UR - http://www.scopus.com/inward/record.url?scp=70849103450&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70849103450&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04592-9_28
DO - 10.1007/978-3-642-04592-9_28
M3 - Conference contribution
AN - SCOPUS:70849103450
SN - 364204591X
SN - 9783642045912
VL - 5712 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 220
EP - 227
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
Y2 - 28 September 2009 through 30 September 2009
ER -