Counting People Using Blobs and Contours
Shafraz Subdurally, Devin Dya, Sameerchand Pudaruth · International Journal of Computer Vision and Image Processing · 2013
Counting the number of people in public locations has become imperative in surveillance applications for the good management of public space. The automatic counting of people can indeed help carry out the above tasks better and faster. In this paper, the authors propose two systems for counting people from images. Their proposed methods are based on the observation that heads are significantly more visible than any other features and are thus more easily distinguishable. The proposed systems use blobs and contour detection respectively to count the number of people. The results obtained from each system are very reliable. The average head detection rate of the systems is 82 and 84 percent respectively.