Coverage Estimation in Heterogeneous Visual Sensor Networks

Abstract

Coverage estimation is one of the fundamental issues in many applications of sensor networks. Coverage estimation in visual sensor networks (VSNs) is more challenging than in conventional 1-D scalar sensor networks (SSNs) due to the directional sensing characteristic of cameras and the existence of visual occlusions in crowded environments. Moreover, deployment of heterogeneous visual sensors and existence of heterogeneous targets in the sensing field makes the coverage estimation problem even more challenging. In this paper, we study the coverage estimation problem in heterogeneous VSNs. We first investigate into a new target detection model, referred to as the "certainty-based target detection" as compared to the traditional "occupancy-based target detection" to facilitate the formulation of the visual coverage estimation. By adopting the new target detection model, we then derive the closed-form solution for the visual coverage estimation problem in heterogeneous VSNs. Our formulation also allows us to take both the presence of visual occlusions and boundary effect into consideration. Results from simulation validate the theoretical formulation, especially when the boundary effect is considered.