A bio-inspired multi-camera system for dynamic crowd analysis

Analysis of crowd density has emerged nowadays as a hot topic issue related to the crowd safety and comfort and directly depended on the design and the operation of the crowded places under study. Usually multiple camera networks are employed to cover, monitor and improve the safety of people in large multifunctional crowded buildings. On the other hand, the art gallery problem is a computational geometry approach to a classical real-world visibility challenge. In a nutshell, it concerns the minimization of the free moving guards required to observe the entire gallery. In this paper we attempt to approach this problem from a novel perspective. To begin with, the number of guards are replaced by multiple cameras whose number should be minimized. At the same time, the observability of the camera network in the available space should be dynamically maximized, so as to observe the evolving density of the crowded areas adequately. In order to achieve this objective a twofold bio-inspired method is described and implemented, based on the emergent computation of swarms to come up with solutions in complex mathematical problems. More specifically, the observations on bumblebee colonies lead us firstly to the definition of artificial bumblebee agents used to determine the number of cameras needed to maximize the observability of a space given the safety specifications emerged from the crowd analysis. Secondly, the way the spiders wave their webs was used as a source of inspiration to determine the exact positions of the cameras in the given space by artificial spider agents. The feedback of the algorithm is then used to cover the areas with significant crowd density in a dynamic fashion. Experimental results show that the algorithm is capable of producing promising results where the areas with the maximum crowd density are continuously detected and covered in a dynamic way.