Optimal Placement of Cameras in Floorplans to Satisfy Task Requirements and Cost Constraints

In many multi-camera vision systems the effect of camera locations on the task-specific quality of service is ignored. Researchers in Computational Geometry have proposed elegant solutions for some sensor location problem classes. Unfortunately, these solutions utilize unrealistic assumptions about the cameras’ capabilities that make these algorithms unsuitable for many real-world computer vision applications. In this paper, the general camera placement problem is first defined with assumptions that are more consistent with the capabilities of realworld cameras. Given a floorplan to be observed, the problem is to efficiently compute a camera layout such that certain task-specific constraints are met and with minimal camera setup cost. A solution to this problem is obtained via binary optimization over a discrete problem space. In preliminary experiments the performance of the system is demonstrated with two different practical experiments on a real floorplan.