Improvement on moving object tracking method for network video surveillance

Guang-xing HAN; Chong-rong LI

doi:10.3969/j.issn.1000-436x.2014.z1.031

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Improvement on moving object tracking method for network video surveillance

Digital campus aand its application | 更新时间：2024-06-05

- Improvement on moving object tracking method for network video surveillance
- Journal on Communications Vol. 35, Issue Z1, Pages: 160-164(2014)
- 作者机构：
  
  清华大学网络科学与网络空间研究院，北京 100084
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-436x.2014.z1.031
  CLC： TP391.41
- Online First：2014-10，
  
  Published：25 October 2014
- 稿件说明：
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Guang-xing HAN, Chong-rong LI. Improvement on moving object tracking method for network video surveillance[J]. Journal on Communications, 2014, 35(Z1): 160-164.
DOI：

Guang-xing HAN, Chong-rong LI. Improvement on moving object tracking method for network video surveillance[J]. Journal on Communications, 2014, 35(Z1): 160-164. DOI： 10.3969/j.issn.1000-436x.2014.z1.031.

摘要

摘要：针对传统的基于Kalman滤波的MeanShift跟踪算法目标运动速度突然改变时跟踪丢失的问题，在Kalman滤波器中引入加速度项使跟踪保持稳定；为了提高Camshift跟踪算法的实时性，使用简化的Camshift算法自适应调整跟踪窗口尺寸。实验结果表明2种改进分别提高了速度突变时跟踪准确性和目标跟踪的实时性，适合网络视频监控场景。

Abstract

To improve the performance of the traditional MeanShift algorithm based on Kalman filter

acceleration to solve the problem that the moving target changes the direction abruptly is proposed.Another algorithm using simplified Camshift algorithm to keep track of the blob size has low time complexity which meets the real time requirement of network video surveillance.

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references

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