Line-based SLAM considering prior distribution of distance and angle of line features in an urban environment

Kei Uehara, Hideo Saito, Kosuke Hara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a line-based SLAM from an image sequence captured by a camera mounted on a vehicle in consideration with the prior distribution of line features that detected in an urban environments. Since such scenes captured by the vehicle in urban envirounments can be expected to include a lot of line segments detected from road markings and buildings, we employ line segments as features for our SLAM. We use additional prior regarding the line segments so that we can improve the accuracy of the SLAM. We assume that the angle of the vector of the line segments to the vehicle’s direction of travel conform to four-component Gaussian mixture distribution. We define a new cost function considering the prior distribution and optimize the relative camera pose, position, and the 3D line segments by bundle adjustment. The prior distribution is also extended into 2D, the distance and angle of the line segments. In addition, we make digital maps from the detected line segments. Our method increases the accuracy of localization and corrects tilted lines in the digital maps. We apply our method to both the single-camera system and the multi-camera system for demonstrate the accuracy improvement by the prior distribution of distance and angle of line features.

Original languageEnglish
Title of host publicationComputer Vision, Imaging and Computer Graphics – Theory and Applications - 12th International Joint Conference, VISIGRAPP 2017, Revised Selected Papers
EditorsPaul Richard, Alexandru Telea, Takehiko Yamaguchi, Alain Tremeau, Dominique Bechmann, Ana Paula Cláudio, Lars Linsen, Francisco Imai
PublisherSpringer Verlag
Pages105-127
Number of pages23
ISBN (Print)9783030122089
DOIs
Publication statusPublished - 2019 Jan 1
Event12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 - Porto, Portugal
Duration: 2017 Feb 272017 Mar 1

Publication series

NameCommunications in Computer and Information Science
Volume983
ISSN (Print)1865-0929

Other

Other12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017
CountryPortugal
CityPorto
Period17/2/2717/3/1

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Keywords

  • Gaussian distribution
  • Line-based SLAM
  • Manhattan world assumption
  • Road markings

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Cite this

Uehara, K., Saito, H., & Hara, K. (2019). Line-based SLAM considering prior distribution of distance and angle of line features in an urban environment. In P. Richard, A. Telea, T. Yamaguchi, A. Tremeau, D. Bechmann, A. P. Cláudio, L. Linsen, & F. Imai (Eds.), Computer Vision, Imaging and Computer Graphics – Theory and Applications - 12th International Joint Conference, VISIGRAPP 2017, Revised Selected Papers (pp. 105-127). (Communications in Computer and Information Science; Vol. 983). Springer Verlag. https://doi.org/10.1007/978-3-030-12209-6_6