Structureless pose-graph loop-closure with a multi-camera system on a self-driving car

Gim Hee Lee, Friedrich Fraundorfer, Marc Pollefeys

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

Abstract

In this paper, we propose a method to compute the pose-graph loop-closure constraints using multiple non/minimal overlapping field-of-views cameras mounted rigidly on a self-driving car without the need to reconstruct any 3D scene points. In particular, we show that the relative pose with metric scale between two loop-closing pose-graph vertices can be directly obtained from the epipolar geometry of the multicameras system. As a result, we avoid the additional time complexities and uncertainties from the reconstruction of 3D scene points which are needed by standard monocular and stereo approaches. In addition, there is a greater flexibility in choosing a configuration for the multi-camera system to cover a wider field-of-view so as to avoid missing out any loop-closure opportunities. We show that by expressing the point correspondences between two frames as Plucker lines and enforcing the planar motion constraint on the car, we are able to use multiple cameras as one and formulate the relative pose problem for loop-closure as a minimal problem which requires 3-point correspondences that yields up to six real solutions. The RANSAC algorithm is used to determine the correct solution and for robust estimation. We verify our method with results from multiple large-scale real-world data.

LanguageEnglish
Title of host publicationIROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages564-571
Number of pages8
DOIs
StatusPublished - 2013
Event2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
Duration: 3 Nov 20138 Nov 2013

Conference

Conference2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
CountryJapan
CityTokyo
Period3/11/138/11/13

Fingerprint

Railroad cars
Cameras
Geometry
Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Lee, G. H., Fraundorfer, F., & Pollefeys, M. (2013). Structureless pose-graph loop-closure with a multi-camera system on a self-driving car. In IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 564-571). [6696407] DOI: 10.1109/IROS.2013.6696407

Structureless pose-graph loop-closure with a multi-camera system on a self-driving car. / Lee, Gim Hee; Fraundorfer, Friedrich; Pollefeys, Marc.

IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2013. p. 564-571 6696407.

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

Lee, GH, Fraundorfer, F & Pollefeys, M 2013, Structureless pose-graph loop-closure with a multi-camera system on a self-driving car. in IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems., 6696407, pp. 564-571, 2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013, Tokyo, Japan, 3/11/13. DOI: 10.1109/IROS.2013.6696407
Lee GH, Fraundorfer F, Pollefeys M. Structureless pose-graph loop-closure with a multi-camera system on a self-driving car. In IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2013. p. 564-571. 6696407. Available from, DOI: 10.1109/IROS.2013.6696407
Lee, Gim Hee ; Fraundorfer, Friedrich ; Pollefeys, Marc. / Structureless pose-graph loop-closure with a multi-camera system on a self-driving car. IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2013. pp. 564-571
@inproceedings{baf3c4fec4c14a95a30509b49d4fd187,
title = "Structureless pose-graph loop-closure with a multi-camera system on a self-driving car",
abstract = "In this paper, we propose a method to compute the pose-graph loop-closure constraints using multiple non/minimal overlapping field-of-views cameras mounted rigidly on a self-driving car without the need to reconstruct any 3D scene points. In particular, we show that the relative pose with metric scale between two loop-closing pose-graph vertices can be directly obtained from the epipolar geometry of the multicameras system. As a result, we avoid the additional time complexities and uncertainties from the reconstruction of 3D scene points which are needed by standard monocular and stereo approaches. In addition, there is a greater flexibility in choosing a configuration for the multi-camera system to cover a wider field-of-view so as to avoid missing out any loop-closure opportunities. We show that by expressing the point correspondences between two frames as Plucker lines and enforcing the planar motion constraint on the car, we are able to use multiple cameras as one and formulate the relative pose problem for loop-closure as a minimal problem which requires 3-point correspondences that yields up to six real solutions. The RANSAC algorithm is used to determine the correct solution and for robust estimation. We verify our method with results from multiple large-scale real-world data.",
author = "Lee, {Gim Hee} and Friedrich Fraundorfer and Marc Pollefeys",
year = "2013",
doi = "10.1109/IROS.2013.6696407",
language = "English",
isbn = "9781467363587",
pages = "564--571",
booktitle = "IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems",

}

TY - GEN

T1 - Structureless pose-graph loop-closure with a multi-camera system on a self-driving car

AU - Lee,Gim Hee

AU - Fraundorfer,Friedrich

AU - Pollefeys,Marc

PY - 2013

Y1 - 2013

N2 - In this paper, we propose a method to compute the pose-graph loop-closure constraints using multiple non/minimal overlapping field-of-views cameras mounted rigidly on a self-driving car without the need to reconstruct any 3D scene points. In particular, we show that the relative pose with metric scale between two loop-closing pose-graph vertices can be directly obtained from the epipolar geometry of the multicameras system. As a result, we avoid the additional time complexities and uncertainties from the reconstruction of 3D scene points which are needed by standard monocular and stereo approaches. In addition, there is a greater flexibility in choosing a configuration for the multi-camera system to cover a wider field-of-view so as to avoid missing out any loop-closure opportunities. We show that by expressing the point correspondences between two frames as Plucker lines and enforcing the planar motion constraint on the car, we are able to use multiple cameras as one and formulate the relative pose problem for loop-closure as a minimal problem which requires 3-point correspondences that yields up to six real solutions. The RANSAC algorithm is used to determine the correct solution and for robust estimation. We verify our method with results from multiple large-scale real-world data.

AB - In this paper, we propose a method to compute the pose-graph loop-closure constraints using multiple non/minimal overlapping field-of-views cameras mounted rigidly on a self-driving car without the need to reconstruct any 3D scene points. In particular, we show that the relative pose with metric scale between two loop-closing pose-graph vertices can be directly obtained from the epipolar geometry of the multicameras system. As a result, we avoid the additional time complexities and uncertainties from the reconstruction of 3D scene points which are needed by standard monocular and stereo approaches. In addition, there is a greater flexibility in choosing a configuration for the multi-camera system to cover a wider field-of-view so as to avoid missing out any loop-closure opportunities. We show that by expressing the point correspondences between two frames as Plucker lines and enforcing the planar motion constraint on the car, we are able to use multiple cameras as one and formulate the relative pose problem for loop-closure as a minimal problem which requires 3-point correspondences that yields up to six real solutions. The RANSAC algorithm is used to determine the correct solution and for robust estimation. We verify our method with results from multiple large-scale real-world data.

UR - http://www.scopus.com/inward/record.url?scp=84893786506&partnerID=8YFLogxK

U2 - 10.1109/IROS.2013.6696407

DO - 10.1109/IROS.2013.6696407

M3 - Conference contribution

SN - 9781467363587

SP - 564

EP - 571

BT - IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

ER -