A Monocular Visual Odometry Method Based on Virtual-Real Hybrid Map in Low-Texture Outdoor Environment
Open Access
Abstract
With the extensive application of robots, such as unmanned aerial vehicle (UAV) in exploring unknown environments, visual odometry (VO) algorithms have played an increasingly important role. The environments are diverse, not always textured, or low-textured with insufficient features, making them challenging for mainstream VO. However, for low-texture environment, due to the structural characteristics of man-made scene, the lines are usually abundant. In this paper, we propose a virtual-real hybrid map based monocular visual odometry algorithm. The core idea is that we reprocess line segment features to generate the virtual intersection matching points, which can be used to build the virtual map. Introducing virtual map can improve the stability of the visual odometry algorithm in low-texture environment. Specifically, we first combine unparallel matched line segments to generate virtual intersection matching points, then, based on the virtual intersection matching points, we triangulate to get a virtual map, combined with the real map built upon the ordinary point features to form a virtual-real hybrid 3D map. Finally, using the hybrid map, the continuous camera pose estimation can be solved. Extensive experimental results have demonstrated the robustness and effectiveness of the proposed method in various low-texture scenes.Keywords
Funding Information
- National Natural Science Foundation of China (62073262, 61672429)
This publication has 30 references indexed in Scilit:
- S-PTAM: Stereo Parallel Tracking and MappingRobotics and Autonomous Systems, 2017
- Large scale and long standing simultaneous reconstruction and segmentationComputer Vision and Image Understanding, 2017
- Accurate and Linear Time Pose Estimation from Points and Lines2016
- Structure-from-Motion Revisited2016
- Stereo visual odometry in urban environments based on detecting ground featuresRobotics and Autonomous Systems, 2016
- StructSLAM: Visual SLAM With Building Structure LinesIEEE Transactions on Vehicular Technology, 2015
- An efficient and robust line segment matching approach based on LBD descriptor and pairwise geometric consistencyJournal of Visual Communication and Image Representation, 2013
- Edge landmarks in monocular SLAMImage and Vision Computing, 2009
- LSD: A Fast Line Segment Detector with a False Detection ControlIEEE Transactions on Pattern Analysis and Machine Intelligence, 2008
- EPnP: An Accurate O(n) Solution to the PnP ProblemInternational Journal of Computer Vision, 2008