Abstract: In response to the challenge of measuring outdoor metal containers, characterized by their large size, weak texture, and complex surrounding environments, a novel measurement method for outdoor weak-textured metals based on multi-view dense reconstruction is proposed. This method achieves dimensional measurement by obtaining a three-dimensional characterization of the weak-textured metal surface. Initially, the traditional incremental structure from motion (SfM) algorithm is improved by introducing a new weighted connected graph, a degree-based initial match pair selection method, and a new viewpoint selection method based on the distribution of visible points, thereby increasing the density of sparse reconstruction. Subsequently, to address the issue of high-quality reconstruction in weak-textured metal areas, a depth estimation method based on sparse priors and a multi-resolution multi-window depth estimation framework are proposed. Experimental results demonstrate that the method presented in this paper can resolve the measurement challenges associated with outdoor weak-textured metals, with an absolute measurement error of 0.52 mm over a distance of 970 mm.

Key words: multi-view 3D reconstruction, motion recovery structure, multi-view stereo, dense point cloud, weakly textured metals