›› 2016, Vol. 29 ›› Issue (3): 75-.

• 论文 • 上一篇    下一篇

医院监控场景下的人群密度估计方法

禹明娟,张英烈,陈临强   

  1. (杭州电子科技大学 计算机学院,浙江 杭州 310018)
  • 出版日期:2016-03-15 发布日期:2016-03-18
  • 作者简介:禹明娟(1990—),女,硕士研究生。研究方向:视频图像处理。

Crowd Density Estimation Method for Hospital Surveillance

YU Mingjuan,ZHANG Yinglie,CHEN Linqiang   

  1. (School of Computer Science,Hangzhou Dianzi University,Hanghzhou 310018,China)
  • Online:2016-03-15 Published:2016-03-18

摘要:

人群密度估计是智能化人群监控中的重要内容,在公共安防、管理控制和商业决策等方面起着重要作用。文中针对医院应用场景,采用一种基于分块的方法,对每一个子图像分别利用基于像素特征与最小二乘直线拟合方法进行人数定量分析和基于灰度共生矩阵与支持向量机的方法进行密度定性分析,得到整幅图像中不同子图及整幅图像的人数和密度分布图。实验表明,该方法能有效的提高人群密度估计的准确率,且还能对局部的密度异常精准定位。

关键词: 人群密度估计, 医院, 最小二乘法, 灰度共生矩阵, 支持向量机

Abstract:

Crowd density estimation,with increasing attention,is the primary content of intelligent crowd surveillance.It plays an important role in the public security,management control as well as business decision.In this paper,we apply it in the situation of hospital with partition methods.We firstly divide the crowd image to sub images.Then for every sub image,we conduct quantitative analysis to the number of people with the function based on pixel feature and least-square line regression respectively.We also conduct a qualitative analysis of the density of people with the function based on gray level co-occurrence matrix (GLCM) and support vector machine (SVM).The number and density distribution of different sub images included in the whole image are obtained for real-time monitoring of the number of people in hospital with accurate location of the local density abnormity.

Key words: crowd density estimation;the situation of hospital;least squares method;GLCM;SVM

中图分类号: 

  • TP391.41