Security is a primary concern in the research and design of tomorrow's intelligent spaces and multi-camera surveillance systems have generated growing interest recently. Due to their advantages of enlarged surveillance area, robustness, enhanced monitoring performance and relatively low cost, they are very suitable for applications in visual security for both indoor and outdoor environments, such as banks, shopping malls, subway stations and parking lots. In a system that employs multiple sensors, the problem of selecting the most appropriate sensor or set of sensors to perform a certain task often arises. This paper represents a critical review on the available techniques for image and segmentation quality assessment for video surveillance applications.
