Surface reconstruction from image space adjacency of lines using breadth first plane search
In this paper, we propose a novel multi view method for surface reconstruction from matched line segments with applications to robotic mapping and image based rendering. Starting from 3D line segments and poses obtained via Line SLAM, we project segments from multiple frames into keyframes for image space analysis. For each keyframe, a grid of image faces is created by optimized intersection of the segment projection lines. These faces define a segment adjacency graph, wherein we perform our Breadth First Plane Search (BFPS) The found plane hypotheses are merged maximally with respect to a structure preserving criterion by growing coplanar regions across the graph. Hypotheses violating the visibility constraint are discarded based on fast per face and mostly nongeometrical evaluation of the scene and image graph. Finally, each image face gets back projected onto an optimal plane to obtain a 3D surface model. The presented system is a complete and automatic solution suitable for mapping an environment in real time scenarios like robotic exploration. We demonstrate the performance of our algorithm on several indoor scenes of varying complexity. Compared to a pure 3D analysis of segments, we see a speed up by one to almost two orders of magnitude, while still improving on reconstruction accuracy.
2016 IEEE International Conference on Robotics and Automation (ICRA)