多车辆跟踪时目标粘连的解决方法

Method for Touching Objects in Multi-vehicle Tracking

复杂交通中车辆间的相互遮挡会造成图像中的车辆粘连,针对这一问题,提出了一种新的基于Kalman预测模型与正交投影定位理论的多运动目标分割与跟踪方法.利用粘连车辆在时域上的历史运动信息和Kalman预测结果,在二值图像中构建特定粘连车辆的分割窗;在分割窗内利用水平-垂直正交投影和动态阈值的理论方法,确定目标最小外接矩形.设计目标分割评判函数,确定粘连车辆分割的合理性,并给出相应的处理结果.实验结果表明,该方法能够有效处理目标相互粘连的情况,实现目标的稳定准确跟踪,并且计算复杂度低,能够满足实时环境的需求.

Based on the Kalman predictive model and orthogonal projection locating theory, a novel algorithm is proposed to segment the object from overlapped vehicle images, which is partly hidden by other object （s）. In the algorithm, a segmentation window is framed for a specific occluding vehicle in binary image by means of the vehicle＇ s historically motion information in time domain and Kalman predictive result, and then the minimal circumscribed rectangle of the vehicle is determined using horizontal-vertical orthogonal projection and dynamic threshold theory. A function is designed to evaluate if the segmentation is reasonable with corresponding results given. Experimental results showed that this algorithm can effectively segment overlapped vehicles from each other and track them steadily with low computational complexity available to meet the requirements for real-time system.