Crowd Density Estimation Method for Hospital Surveillance
YU Mingjua · Electronic Science and Technology · 2016
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.