Abstract

An algorithm for detecting and tracking moving people on video sequences using the block optical flow method and motion maps is proposed. To reduce time expenditures, a pyramidal representation of the frame and template search are used at the stage of building a preliminary map of motion vectors. The integral optical flow allows one to reduce the resulting amplitudes of the background displacement vectors and increase the resulting amplitudes of the displacement vectors of foreground objects. To improve the accuracy for localization of objects, the additive minimax similarity function is used in the analysis of motion vectors. Objects are tracked based on a modified tracing algorithm using the Kalman filter. The developed algorithm allows one not only to detect a moving object but also to show the trajectory of its movement. The results of experiments are presented that allow evaluating the effectiveness of the algorithm.

中文翻译：

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基于光流块法和运动图的视频中人的运动估计

摘要

提出了一种利用块光流法和运动图检测和跟踪视频序列上运动人物的算法。为了减少时间花费，在构建运动矢量的初步图的阶段使用了帧的金字塔形表示和模板搜索。积分光流允许减少背景位移矢量的合成幅度并增加前景物体的位移矢量的合成幅度。为了提高目标定位的准确性，在运动矢量分析中使用了加性极小极大相似度函数。使用卡尔曼滤波器根据修改后的跟踪算法跟踪对象。开发的算法不仅可以检测运动物体，还可以显示其运动轨迹。