Camera placement using particle swarm optimization in visual surveillance applications

In this paper, we propose a novel approach to automatically plan video cameras positioning in indoor environments for surveillance applications. In order to ensure maximum coverage of the observed scene, we have implemented an ad-hoc tool based on the particle swarm optimization. The camera is modeled as a 2D function. A Rayleigh distribution is used to characterize the relevance of the observed object with respect to the distance from the camera and a Gaussian distribution is adopted to model the horizontal field-of-view. Knowing the environment characteristics and the location of obstacles and walls, it is possible to derive a reliable positioning of the sensors. Results are first presented for very simple scenarios; the algorithm is then run to solve the problem in a more realistic environment model.