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首页> 外文会议>2013 Seventh International Conference on Distributed Smart Cameras >3D pedestrian tracking based on overhead cameras
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3D pedestrian tracking based on overhead cameras

机译：基于高架摄像机的3D行人跟踪

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This paper proposes a method to track pedestrians in crowded scenes based on the detection of the 3D head position of a person using two overhead cameras. A possible head area in one frame acquired from one of the overhead cameras is determined by evaluating a head area existence probability based on the integral polar mapped image, where a foreground pixel is assigned a probability to belong to the head area. A segment passing through the head top is estimated for each clustered head area. The disparities along each segment are calculated using the synchronized frame from the other overhead camera. The center of the points with the largest disparity on the segment is determined as the head point and its 3D position is computed using triangulation. It is then tracked using common assumptions on motion direction and velocity. This is efficiently done notwithstanding the fact that several segments may exist in a single foreground blob with each segment corresponding to a different person. The approach is tested using a publicly available visual surveillance simulation test bed. The experiments show that the 3D tracking errors are around 5 cm. The method allows for the capture of high quality close-up facial images.
机译：本文提出了一种使用两个高架摄像机对人的3D头部位置进行检测的跟踪拥挤场景中行人的方法。通过基于积分极性映射图像评估头部区域存在概率，来确定从其中一个高架摄像机获取的一帧中可能的头部区域，其中将前景像素分配给属于头部区域的概率。对于每个聚簇的头部区域，估计经过头部顶部的一段。沿每个线段的视差是使用来自其他高架摄像机的同步帧来计算的。将段上差异最大的点的中心确定为起点，并使用三角测量法计算其3D位置。然后使用关于运动方向和速度的常见假设对其进行跟踪。尽管在单个前景斑点中可能存在多个段，而每个段对应于一个不同的人这一事实仍然有效地做到了。使用公共可见的视觉监控模拟测试台对该方法进行了测试。实验表明3D跟踪误差约为5厘米。该方法允许捕获高质量的特写面部图像。

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