Toward Large Scale Model Construction for Vision-Based Global Localisation

Abstract

Abstract:Monocular SLAM reconstruction algorithm advancements enable their integration in various applications: trajectometry, 3D model reconstruction, etc. However proposed methods still have drift limitations when applied to large-scale sequences. In this paper, we propose a post-processing algorithm which exploits a CAD model to correct SLAM reconstructions. The presented method is based on a specific deformable transformations model and then on an adapted non-rigid ICP between the reconstructed 3D point cloud and the known CAD model. Experimental results on both synthetic and real sequences point out that the 3D scene geometry regains its consistency and that the camera trajectory is improved: mean distance between the reconstructed cameras and the ground truth is less than 1 meter on several hundreds of meters.