Propagation-based Dynamic Topology Estimation Framework for Vision Sensor Networks

摘要

With the recent development of hardware technologies, vision sensor networks (VSNs) are widely deployed to communicate with environments. One of the key issues in a VSN is to build a topology graph and localize vision sensors in the network precisely and dynamically. This paper proposes a framework for estimating a topology graph for a VSN in a dynamic configuration and localizing vision sensors using the topology graph. In the paper, it is assumed that intrinsic parameters of each vision sensor are already known, only one vision sensor is localized, and each vision sensor is overlapped with at least one vision sensor. In order to determine the position and orientation of the rest of the vision sensors, localization information of the localized one in the network is propagated to the rest of vision sensors. The amount of arithmetic calculation needed for the method is small and hence can be adopted to low power processors. The accuracy and reliability of the method have been validated by performing Visual Sensor Network, Localization, Propagation, Dynamic Topology Estimation experiments with real images. The framework has been proven practical on a VSN.