计算机科学 ›› 2013, Vol. 40 ›› Issue (10): 292-295.

• 图形图像与模式识别 • 上一篇    下一篇

基于时空马尔可夫随机场交通参数采集系统研究

周君   

  1. 淮阴工学院交通学院 淮安223003
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(51078085)资助

Research on Traffic Parameter Acquisition System Based on ST-MRF Model

ZHOU Jun   

  • Online:2018-11-16 Published:2018-11-16

摘要: 可靠的车辆跟踪是实现交通事件自动检测的重要前提,车辆跟踪中的车辆相互遮挡则是影响车辆跟踪结果的关键因素。针对这一难题,提出了一种基于时空马尔可夫随机场(简称ST-MRF)模型的车辆跟踪算法,用以得到目标地图和运动矢量地图。在目标地图和运动矢量地图的基础上提取交通参数,然后通过摄像机标定技术,获得实时的车速以及车辆运动坐标,最后通过对交通流三参数的分析,得到实时的交通流运行特征。这可为以后的交通事件检测提供依据。

关键词: 时空马尔可夫随机场,车辆跟踪,交通参数,目标地图,运动矢量地图

Abstract: Robust vehicle tracking algorithm is an important precondition for realizing traffic event detection,but occlusion is a key influence factor for vehicle tracking.An adaptive vehicle tracking algorithm based on spatial temporal Markov random field(be short for ST-MRF)model was proposed to deal with the problem .This tracking algorithm is used to acquire the object maps and the motion vector maps.The traffic parameters can be obtained from the object maps and the motion vector maps.Then using the camera calibration technique gets the real time speed,as well as the vehicle motion coordinates.At last,through the analysis of the three parameters of traffic flow,the real-time traffic flow operation characteristics are got,which can provide basis for the traffic incident detection in the future.

Key words: ST- MRF,Vehicle tracking algorithm,Traffic parameter,Object maps,Motion vector maps

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