Camera Network Coverage Improving by Particle Swarm Optimization
1 Institute of Intelligent Vision and Image Information, China Three Gorges University, 443002, Yichang, China
2 Department of Mediamatics, Faculty of Electrical Engineering, Mathematics, and Computer Science (EEMCS) , Delft University of Technology, 2600 GA Delft, The Netherlands
EURASIP Journal on Image and Video Processing 2011, 2011:458283 doi:10.1155/2011/458283Published: 2 December 2010
This paper studies how to improve the field of view (FOV) coverage of a camera network. We focus on a special but practical scenario where the cameras are randomly scattered in a wide area and each camera may adjust its orientation but cannot move in any direction. We propose a particle swarm optimization (PSO) algorithm which can efficiently find an optimal orientation for each camera. By this optimization the total FOV coverage of the whole camera network is maximized. This new method can also deal with additional constraints, such as a variable region of interest (ROI) and possible occlusions in the ROI. The experiments showed that the proposed method has a much better performance and a wider application scope. It can be effectively applied in the design of any practical camera network.