In order to solve the problem of cooperative pose estimation in augmented reality systems, a newcooperative poseestimation method is proposed. Firstly, statistical analysis of the neighborhood of point cloud space is carriedout toimprove the precision of high point cloud segmentation. After point cloud processing, the collaborative pose estimationmodel is established by using centroid to obtain the collaborative pose estimation results. Experimental results showthat the proposed method can effectively obtain collaborative pose estimation results.
With the development of augmented reality technology in the future, its application environment is bound to be complex and diverse, and for some extreme weather scenarios, it is very important to solve the existing problems of optical transmission display system.In addition, solving the above problems is more conducive to improving the user's perception ability of scene information in the environment with low visibility. Therefore, by analyzing the problems existing in the augmented reality display system in extreme weather, this paper proposes a set of augmented reality display system for electric navigation. First, calibrate human eyes, tracking cameras and augmented reality display devices. Aiming at the distortion problem in the display process, a four-dimensional light field calibration theory was established to reduce the display error. The camera is used to obtain the scene information, and the 3D point cloud is obtained. By denoising the 3D point cloud, the instance segmentation algorithm is used to obtain the segmentation result of the scene target. Finally, the virtual image is displayed in the scene to display the navigation information in the power operation. The system can provide clear scene information for power operators in extreme weather conditions, effectively improving work efficiency and safety.
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