The performance of computer vision systems for measurement, surveillance, reconstruction, gait recognition, and many other applications, depends heavily on the placement of cameras observing the scene. This work addresses the question of the optimal placement of cameras to maximize the performance of real-world vision systems in a variety of applications. Specifically, our goal is to optimize the aggregate observability of the tasks being performed by the subjects in an area. We develop a general analytical formulation of the observation problem, in terms of the statistics of the motion in the scene and the total resolution of the observed actions that is applicable to many observation tasks and multi-camera systems. An optimization approach is used to find the internal and external (mounting position and orientation) camera parameters that optimize the observation criteria. We demonstrate the method for multi-camera systems in real-world monitoring applications, both indoor and outdoor.
['Robert Bodor', 'Paul R. Schrater', 'Nikolaos Papanikolopoulos']
Multi-camera positioning to optimize task observability