A Genetic Optimization Method for Spatial Layout of Cameras in Video Sensor Networks

Video sensor networks consist of cameras to monitor targets and play an important role in monitoring and analysis of agriculture, security management and emergency rescue, etc. However, traditional methods for camera placement result in little effective monitoring area and low utilization rate of cameras. To solve these problems, we propose a method for optimizing the spatial layout of cameras in video sensor networks based on the genetic algorithm. First, candidate layout positions of cameras were selected according to the oblique photogrammetry 3D model. Secondly, we calculated and selected the best orientation of cameras and encoded cameras. Then, the visible area of all cameras was calculated. Finally, the best video sensor network with genetic algorithm optimization was formed. The simulation results show the algorithm effectively improves the visibility of cameras, achieves larger area with fewer cameras and reduces cost while increasing the utilization of cameras.