关键词: 交通流量采集, 背景提取, 贝叶斯算法, 运动车辆检测与跟踪

Abstract: Efficient detecting and tracking of vehicles is very important for collecting traffic flow information in intelligent transportation systems. Visual based motion analysis of vehicles is an active research topic of traffic flow estimation which involves detecting, tracking and recognizing from the surveillance image sequences or videos. Efficient and robust vehicle detecting and tracking under the real complex road scene is still a challenge task. This paper presents an efficient traffic flow detection method which firstly extracts foreground image using Bayesian classification algorithm, and then detects vehicle object with background subtraction. The method features low computational load, thus meets the real-time requirements in many practical applications. It tests this method with very low/high quality traffic surveillance videos and gets high detection accuracies.

Key words: traffic flow detection, background detecting, Bayesian classification algorithm, vehicle detecting and tracking