时变人群密度分布可视化的自适应方法

2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) Pub Date : 2018-09-01 DOI:10.23919/SPA.2018.8563391

Marianna Parzych, T. Marciniak, A. Dabrowski

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引用次数: 0

摘要

本文分析了人群密度可视化的可视化方法。生成的密度图考虑了时间的变化。已经实施和测试了三种方法。第一种是基于背景减法的运动检测。第二种是基于blob(二进制大对象)分析。第三种方法是使用兴趣点。图像上可以被物体使用的点跟踪运动。使用PETS2009视频序列数据库进行测试。对获得的地图进行了评估，并估计了时间消耗。

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Adaptive methods of time-dependent crowd density distribution visualization

The paper presents an analysis of visualization methods of crowd density visualization. Generated density maps take into account changes in time. Three methods have been implemented and tested. The first one uses motion detection based on the background subtraction. The second one is based on BLOBs (binary large objects) analysis. The third method uses interest points ie. points on the image that can be used by the object track the movement. The tests were performed using the PETS2009 video sequence database. The obtained maps were evaluated and the time consumptions were estimated.

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来源期刊

2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)

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