Skip to Main Content
Camera sensor networks have recently emerged as a very critical research topic. Target tracking and localization are important applications in camera sensor networks. In this paper, we investigate the coverage problem from the perspective of target localization in camera sensor network, compare to the coverage problem for target detection has been intensively studied. We first propose a novel localization-oriented sensing model based on the perspective projection of the camera. Then, assuming that the camera sensors are deployed as a random uniform process, we study how the probability of the localization- oriented coverage (L-coverage for short) changes with the number of sensors or some other factors. Finally, we use simulations to validate our theoretical analysis and demonstrate the boundary effect on L-coverage probability. The obtained results show that our model can be effectively deployed in practical scenarios.