SLAM-based 3D Line Reconstruction

Abstract

Recovering 3D structure of the scene is widely studied in computer vision, which is called structure from motion. Most of the structure from motion approaches using features points to reconstruct 3D point cloud maps to represent scenes. However, there are always many lines in manmade scenes. Line is a higher-level representation of scene structure than point. We contribute a SLAM (simultaneous location and mapping) based method to reconstruct the 3D lines of urban scenes to emphasize the structures. In our approach, keyframe based SLAM system provides keyframes and camera poses, line segments are extracted and tracked in keyframes, the spatial line is determined in two steps: direction then position. The direction is acquired from normal vectors of multiple line projection planes and depth is searched by minimizing the total re-projection error of a spatial line in multiple keyframes. Degenerate and incorrectly tracked cases are detected by rank and principal components analysis. We present accurate 3D line model for urban scene with UAV inspection. The generated 3D lines give a better structural sense than sparse point cloud.