Vehicle Tracking in Daytime and Nighttime Traffic Surveillance Videos

摘要：

In this work, a vehicle tracking system is developed to deal with daytime and nighttime traffic surveillance videos. For daytime videos, vehicles are detected via background modeling. For nighttime videos, headlights of vehicles need to be located and paired to initialize vehicles for the tracking purpose. An algorithm based on likelihood computation is developed to pair the headlights of vehicles. In addition, we apply a specialized system state transition model of the Kalman filter to adapt to common settings of traffic surveillance cameras. The experimental results have shown that the proposed method can effectively track vehicles in both daytime and nighttime surveillance videos.

关键词： tracking Kalman filler traffic surveillance

作者: Hsu-Yung Cheng Po-Yi Liu Yen-Ju Lai

作者单位: Department of Computer Science and Information Engineering National Central University Jong-Li, Tao-Yuan, Taiwan

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Education Technology and Computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

会议地点: 上海

会议语种:英文

页码: 122-125

在线出版日期: 2010-06-22（万方平台首次上网日期，不代表论文的发表时间）