Illumination modelling and optimization for indoor video surveillance

摘要

Illumination is one of the most important aspects of any surveillance system. The quality of images or videos captured by the cameras heavily depends on the positioning and the intensity of the light sources in the environment. However, exhaustive visualization of the illumination for different placement configurations is next to impossible due to the sheer number of possible combinations. In this paper we propose a novel 3D modelling of a given environment in a synthetic domain, combined with a generic quality metric, is based on entropy measurement in a given image. The synthetic modelling of the environment allows us to evaluate the optimization problem a priori before the physical deployment of the light sources. Entropy is a general measure of the amount of information in an image, so we propose to maximize the entropy out of all possible light placement configurations. In order to model the environment in the virtual domain, we use the POVRAY software, a tool based on ray tracing. Particle swarm optimization is then adopted to find the optimal solution. The total entropy of the system is measured as sum of entropy of the virtual snapshots in the camera system.