关键词: 单目视觉, 半稠密, 三维重建, 同时定位与地图构建, 关键帧再剔除

Abstract:

Building more detailed 3D maps and estimating more accurate camera poses have always been the goal pursued by Simultaneous Localization And Mapping（SLAM） technology. The above goals are contradictory to real-time requirements, low computational cost, and limited computing resource of SLAM. A novel semi-dense 3D reconstruction method based on the monocular Oriented FAST and Rotated BRIEF-SLAM（ORB-SLAM） by using the line segment features extracted from keyframes is proposed. Specifically, the improved method builds upon ORB-SLAM, which first provides a series of map points and a set of keyframes and their corresponding camera poses information in real-time. A Keyframe Re-Culling（KRC） algorithm is proposed to further reduce redundant keyframes. A line segment extraction algorithm is employed to extract line segments in each keyframe. By adopting a purely geometric constraints method to match 2D line segments from different keyframes to generate a semi-dense 3D scene model. Experimental results show that the novel method runs steadily and reliably, and can quickly perform online 3D reconstruction with low computational cost.

Key words: monocular-vision, semi-dense, 3D reconstruction, Simultaneous Localization And Mapping（SLAM）, keyframes re-culling