Crowd detection in airborne images using spatial point statistics

The crowd density in public places increases in social events. If an emergency occurs during such events, authorities should take urgent measures to prevent causalities. Therefore, crowd detection and analysis is a critical research area. Even though there are several studies on person detection from street or indoor cameras, these may not be directly used to detect or analyze the crowd formed from people. In this study, we approach the problem using aerial images. We propose two novel methods to detect the crowd using spatial statistics. The first novel method is based on the first-order statistics. It uses the nearest neighbor relations for each person in the image. The second novel method is based on the second-order statistics. Here, the spatial position of persons are checked whether they are clustered or randomly distributed. We test these two methods on a sample test image and provide performance measures.