Optimal sensor placement for surveillance of large spaces

Visual sensor network design facilitates applications such as intelligent rooms, video surveillance, automatic multi-camera tracking, activity recognition etc. These applications require an efficient visual sensor layout which provides a minimum level of image quality or image resolution. This paper addresses the practical problem of optimally placing the multiple PTZ cameras to ensure maximum coverage of user defined priority areas with optimum values of parameters like pan, tilt, zoom and the locations of the cameras. The proposed algorithm works offline and does not require camera calibration. We mapped this problem as an optimization problem using Genetic Algorithm, by defining, coverage matrix as a set of sensor parameters and the space model parameters like priority areas, obstacles and feasible locations of the sensors, and by modelling discrete spaces using probabilistic frame work. We minimized the probability of occlusion due to randomly moving objects by covering each priority area using multiple cameras. The proposed method will be applicable for surveillance of large spaces with discrete priority areas like a hall with more than one entrance or many events happening at different locations in a hall eg.Casino. As we are optimizing the parameters like pan, tilt, zoom and even the locations of the cameras, the coverage provided by this approach will assure good resolution, which improves the QOS of the visual sensor network.