A Look-up Table Based Approach for Solving the Camera Selection Problem in Large Camera Networks

Modern navigation, mapping and surveillance systems require numerous cameras mounted at random locations over a geographically large area. In order to efficiently extract any location-specific intelligence from such a large network of cameras, we propose to create distributed look-up tables that rank the cameras according to how well they can image a specific location. The look-up table covers all possible locations within the corresponding camera’s viewing frustum1 by optimally dividing the volume of the viewing frustum. The process of updating look-up tables is purely incremental, thus it can easily be used in a dynamic network. The foremost advantages of our approach are a significant reduction of run-time computation for selecting a set of favorable cameras using a simple lookup operation and a significant reduction of network traffic that would otherwise be required to carry out the process of camera selection. The proposed algorithm can be applied to various applications involving distributed cooperative processing in a large camera network.