A cooperative camera surveillance method based on the principle of coarse-fine coupling boresight adjustment

Abstract Visual surveillance systems play a vital role in smart manufacturing scenes. In this paper, a cooperative camera surveillance method is proposed based on the coarse-fine coupling boresight adjustment principle. A master-slave camera cooperative monitoring model is established by combining a high-resolution camera with a large-field camera, the former of which is embedded with a Risley prism pair to perform high-precision boresight pointing for monitoring a local target, while the latter can observe a wide scene and guide the former to catch a region of interest. An effective boresight adjustment strategy is put forward with a method of combining fast convergence and iterative refinement. A calibration method of the master-slave camera is proposed with the combination of binocular vision and equivalent motion plane. The error distribution, adjustment efficiency and tracking accuracy of the dual field monitoring are analyzed in detail to reveal the mapping mechanism between imaging feedback and boresight adjustment. In the surveillance experiment, the root-mean-square tracking error of the fine tracking camera can achieve better than 7.04 pixels, while the adjustment steps only need about 10 times, which validates the feasibility and effectiveness of the proposed method in industrial operation surveillance.