Vehicle counting systems can help with vehicle analysis and traffic incident detection. Unfortunately, most existing methods require some level of human input to identify the Region of interest (ROI), movements of interest, or to establish a reference point or line to count vehicles from traffic cameras. This work introduces a method to count vehicles from traffic videos that automatically identifies the ROI for the camera, as well as the driving trajectories of the vehicles. This makes the method feasible to use with Pan-Tilt-Zoom cameras, which are frequently used in developing countries. Preliminary results indicate that the proposed method achieves an average intersection over the union of 57.05% for the ROI and a mean absolute error of just 17.44% at counting vehicles of the traffic video cameras tested.

翻译：不幸的是,大多数现有方法都需要一定的人力投入,才能确定感兴趣的区域(ROI)、有关移动、或建立参照点或路线,以便从交通摄像头中计数车辆。这项工作采用了一种从交通录像中计数车辆的方法,自动识别相机的ROI以及车辆的驾驶轨迹。这使得使用在发展中国家常用的泛式Zoom照相机的方法是可行的。初步结果表明,拟议方法在所测试的交通摄像头的车辆总和57.05%上达到平均交叉点,在计算所测试的交通摄像头的车辆时仅出现17.44%的绝对误差。