3D visual correlation model for wireless visual sensor networks

Abstract

Wireless visual sensor networks comprise a large number of camera-equipped sensor devices and obtain visual information from field of interest. In a Wireless visual sensor network, there exist visual correlation characteristics among images observed by cameras with overlapped field of views. To describe those characteristics, the conventional method is based on image processing. However, it is too complex to be applied to cameras in resource-constrained wireless visual sensor networks. In this paper, based on 3D sensing model and coordinate transformation theory, a novel 3D visual correlation model is designed to exploit the correlation characteristics among cameras for spatial wireless visual sensor networks. The designed model, of which a visual correlation function was proposed, and then a 3D visual correlation coefficient algorithm is derived. Experimental results demonstrated that the designed model can accurately model the visual correlation characteristics and the proposed 3D visual correlation coefficient algorithm outperforms the state-of-the-art algorithms.