Fast line description for line-based SLAM

Keisuke Hirose, Hideo Saito

Research output: Contribution to conferencePaperpeer-review

48 Citations (Scopus)


Simultaneous localization and mapping (SLAM) is a technique to simultaneously perform mapping of environments and localization of a camera in real-time. Most existing monocular vision based SLAM techniques use point features as landmarks. However, images of artificial environments with little texture often contain many line segments, whereas few point features can be localized in such a scene. We propose here a realtime line-based SLAM system, and a novel method for describing the features of line segments (LEHF:Line-based Eight-directional Histogram Feature) in order to establish correct 2D and 3D line correspondences (2D-3D correspondences). LEHF is a fast and efficient way of describing features of line segments, which are detected by the line segment detector (LSD) method. The line-based orthogonal iteration (LBOI) method and the RANSAC algorithm are applied for the camera pose estimation. We conducted an experiment in order to test our SLAM system in a desktop environment and to perform augmented reality (AR). Moreover our SLAM system was evaluated by synthetic data.

Original languageEnglish
Publication statusPublished - 2012
Event2012 23rd British Machine Vision Conference, BMVC 2012 - Guildford, Surrey, United Kingdom
Duration: 2012 Sept 32012 Sept 7


Other2012 23rd British Machine Vision Conference, BMVC 2012
Country/TerritoryUnited Kingdom
CityGuildford, Surrey

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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