PL SVO: Semi direct Monocular Visual Odometry by combining points and line segments
Most approaches to visual odometry estimates the camera motion based on point features, consequently, their performance deteriorates in low textured scenes where it is difficult to find a reliable set of them. This paper extends a popular semi direct approach to monocular visual odometry known as SVO [1] to work with line segments, hence obtaining a more robust system capable of dealing with both textured and structured environments. The proposed odometry system allows for the fast tracking of line segments since it eliminates the necessity of continuously extracting and matching features between subsequent frames. The method, of course, has a higher computational burden than the original SVO, but it still runs with frequencies of 60Hz on a personal computer while performing robustly in a wider variety of scenarios.
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)