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Capturing the Dynamics of Pedestrian Traffic Using a Machine Vision System

机译：使用机器视觉系统捕捉行人动态

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We developed a machine vision system to automatically capture the dynamics of pedestrians under four different traffic scenarios. By considering the overhead view of each pedestrian as a digital object, the system processes the image sequences to track the pedestrians. Considering the perspective effect of the camera lens and the projected area of the hallway at the top-view scene, the distance of each tracked object from its original position to its current position is approximated every video frame. Using the approximated distance and the video frame rate (30 frames per second), the respective velocity and acceleration of each tracked object are later derived. The quantified motion characteristics of the pedestrians are displayed by the system through 2-dimensional graphs of the kinematics of motion. The system also outputs video images of the pedestrians with superimposed markers for tracking. These visual markers were used to visually describe and quantify the behavior of the pedestrians under different traffic scenarios.
机译：我们开发了一种机器视觉系统，可以自动捕获四种不同交通场景下行人的动态。通过将每个行人的俯视图视为数字对象，系统处理图像序列以跟踪行人。考虑到摄像机镜头的透视效果以及顶视图场景的走廊投影区域，每个视频帧都近似于每个被跟踪对象从其原始位置到当前位置的距离。使用近似的距离和视频帧速率（每秒30帧），随后可以得出每个被跟踪对象的速度和加速度。系统通过运动运动学的二维图形显示行人的量化运动特征。该系统还输出带有叠加标记的行人视频图像以进行跟踪。这些视觉标记用于在视觉上描述和量化不同交通场景下行人的行为。

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