Research on Estimation Algorithm of Crowd Counting Based on Fisheye Video Image
Han Yinghu · 2014
In some public places,the statistics about the number of people is an important problem in security field.In order to receive large perspective,to get more useful video information,considering real-time and monitoring costs,this paper used a fisheye lens to monitor population. In order to make all the field of view imaging features image in the finite size of the surface,the designer introduced the barrel distortion artificially. At the same time,because the actual scenery through a fisheye lens,will produce the pixels with different weight,in the process of crowd counting based on fisheye video image,four features including weighted area,weighted edge density,weighted KLT corner number and weighted contour perimeter are extracted based on the perspective weight model of fisheye camera,and polynary linear regression combined with these features is applied for crowd counting in fisheye images.The experimental results are quite good.