Comparison of Person Tracking Algorithms Using Overhead View Implemented in OpenCV

K. Ullah, Imran Ahmed, Misbah Ahmad, I. Khan
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引用次数: 7

Abstract

As computer based technologies are growing rapidly, new problems are arising, which need serious and urgent attentions. Person tracking is one of the typical computer vision problem which is the center of interest for researchers working on surveillance systems (industries, shopping malls, educational institutions and hospitals etc. In this research work, a top view camera has been installed with a wide angle lens able to cover a wide area and more information for surveillance and visual monitoring purposes. Some of the common issues that are addressed in this research work are occlusion, sudden change in movement, tracking standstill body, abrupt change in direction, varying lightening conditions and differentiating a person from other objects. In this paper, different tracking algorithms are compared on a newly developed dataset using OpenCV. These algorithms are pre-implemented in the popular OpenCV library. The results and efficiency of these algorithms on a new data set are also discussed. All these algorithms give different results on overhead and frontal view video sequences.
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OpenCV实现的基于俯视图的人员跟踪算法比较
随着计算机技术的迅速发展,出现了许多新的问题,需要认真而迫切地加以重视。人的跟踪是典型的计算机视觉问题之一,是监控系统(工业、商场、教育机构和医院等)研究人员感兴趣的中心问题。在本研究工作中,安装了一种具有广角镜头的顶视图摄像机,可以覆盖更广的区域和更多的信息,用于监视和视觉监控。在这项研究工作中解决的一些常见问题是遮挡、运动的突然变化、跟踪静止的身体、方向的突然变化、光照条件的变化以及人与其他物体的区分。本文在OpenCV新开发的数据集上比较了不同的跟踪算法。这些算法是在流行的OpenCV库中预先实现的。讨论了这些算法在新数据集上的效果和效率。所有这些算法在俯视图和正面视图视频序列上给出了不同的结果。
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