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Realtime person tracking by integrating optical flow and uniform brightness regions

机译:通过集成光流和均匀亮度区域的实时人员跟踪

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摘要

This paper describes a method of realtime person tracking in a cluttered background by integrating optical flow and uniform brightness regions. Optical flow is extracted at points with enough contrast in an image. Assuming that the target person moves at a sufficiently large angle to the optical axis, the target can be detected in the image as a region where flow vectors are nearly uniform. Uniform brightness regions are extracted as connected points where optical flow cannot be obtained due to lack of contrast. At each frame, tracking is performed by continuously updating the flow and the uniform brightness regions of the target based on the prediction of those regions by using the target motion in the image. As long as, at least, one of these visual cues is effective to distinguished from the background and other objects, the target person can be tracked. Our proposed method was implemented on a realtime image processor with multiple DSPs and successfully tracked a target person in realtime.
机译:本文通过集成光流和均匀的亮度区域,介绍了一种实时人物在杂乱的背景中跟踪的方法。在图像中以足够对比度的点提取光流量。假设目标人以足够大的角度移动到光轴,则可以在图像中检测到目标作为流动矢量几乎均匀的区域。均匀的亮度区域被提取为连接点,其中由于缺乏对比度而不能获得光学流动。在每个帧处,通过使用图像中的目标运动连续地更新目标的预测来执行跟踪来执行跟踪来执行。只要至少,这些视觉线索中的一个有效地与背景和其他对象区分开来,可以跟踪目标人物。我们所提出的方法在具有多个DSP的实时图像处理器上实现,并成功地将目标人实时跟踪。

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