Collaborative node localization in surveillance networks using opportunistic target observations

A collaborative vision-based technique is proposed for localizing the nodes of a surveillance network based on observations of a non-cooperative moving target. The proposed method employs lightweight in-node image processing and limited data exchange between the nodes to determine the positions and orientations of the nodes participating in synchronized observations of the target. A node with an opportunistic observation of a passing target broadcasts a synchronizing packet and triggers image capture by its neighbors. In the cluster of participating nodes, the triggering node and a helper node define a relative coordinate system. Once a small number of joint observations of the target are made by the nodes, the model allows for a decentralized or a clusterbased solution for the localization problem. No images are transferred between the network nodes for the localization task, making the proposed method efficient and scalable. Simulation and experimental results are provided to verify the performance of the proposed technique