一种从人群视频中计数和跟踪人群的新方法

2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2017-07-03 DOI:10.1109/INISTA.2017.8001170

Merve Ayyuce Kizrak Sagun, B. Bolat

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引用次数: 7

摘要

视频录像的人群分析是目前一个重要的研究领域。本文提出了一种组合人群密度估计方法来克服这一问题。为了提高系统的准确性，两个不同的估计器同时运行，并且只有当两个估计器都将blob标记为人时，才将其标记为人。人群密度估计的主要问题之一是遮挡。为了克服这个问题，我们使用卡尔曼滤波来跟踪斑点的轨迹。将该方法应用于PETS2009、UCSD和Grand Central三个常用基准数据。结果证实了该方法的成功。

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A novel approach for people counting and tracking from crowd video

Crowd analysis on video recordings is an important research area currently. In this work, a combined crowd density estimation method is presented to overcome this problem. To improve the accuracy of the system two different estimators run simultaneously and a blob is marked as a person only if both estimators mark it as person. One of the main problems in crowd density estimation is occlusion. To overcome this problem we tracked the trajectories of blobs by using a Kalman filter. The method was applied to three common benchmark data which are PETS2009, UCSD and Grand Central. The results confirm the proposed method's success.

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2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)

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