3D Reconstruction and Pose Estimation of Non-Cooperative Objects Based on Structure From Motion

This paper studies the problem of 3D reconstruction and pose estimation of non-cooperative targets in a space environment with uneven illumination. First, a simulation model of a failed satellite is constructed using SolidWorks to simulate the 3D structure and motion posture of a failed tumbling satellite. The satellite model is rendered with a single light source according to the characteristics of the space environment to construct a synthetic data set with good generalization ability. Then, in order to solve the problems of dark local details and blurred target information in the space environment, local enhancement is performed based on the LIME image enhancement algorithm, and foreground extraction is performed based on the Canny edge detection and morphological algorithm to improve the image quality and feature visibility. Based on the Colmap platform, incremental 3D reconstruction is performed through SIFT feature extraction and matching, triangulation, and bundle adjustment optimization to generate a sparse point cloud model and camera pose. On the basis of the reconstructed point cloud, the principal component analysis method is used to construct the target coordinate system, and the target pose is obtained through coordinate system transformation, which verifies the effectiveness of 3D reconstruction and pose estimation of non-cooperative targets in complex space environments.