On-the-fly Extrinsic Calibration of Non-Overlapping in-Vehicle Cameras based on Visual SLAM under 90-degree Backing-up Parking

Kazuki Nishiguchi, Hideaki Uchiyama, Kazutaka Hayakawa, Jun Adachi, Diego Thomas, Atsushi Shimada, Rin Ichiro Taniguchi

Research output: Contribution to conferencePaperpeer-review

Abstract

Calibration of relative poses between cameras is a challenging problem, known as extrinsic calibration, for nonoverlapping cameras that do not share the field of view. We propose a method for calibrating non-overlapping in-vehicle cameras placed at front, back, left and right positions by using visual SLAM(vSLAM). Our proposal is to calibrate the cameras during the motion of 90-degree backing-up parking on the fly, without using any dedicated calibration equipment. With this motion, the adjacent cameras are able to have the close field of view at different moments. The relative poses can be computed if the maps computed with vSLAM on each camera are merged by using the common structures. Therefore, we propose an efficient calibration framework with this feature. The proposed method is divided into three steps: map reconstruction with vSLAM on each camera, map merging for all the cameras, and extrinsic calibration. Especially, we propose to separately utilize the frames for vSLAM and the ones for the calibration so that the accuracy of vSLAM can be maximized for the calibration. In the evaluation, the calibration was performed in a practical environment to investigate the performance in comparison with the ground truth acquired by using a calibration equipment.

Original languageEnglish
Pages2021-2028
Number of pages8
DOIs
Publication statusPublished - 2020
Event31st IEEE Intelligent Vehicles Symposium, IV 2020 - Virtual, Las Vegas, United States
Duration: Oct 19 2020Nov 13 2020

Conference

Conference31st IEEE Intelligent Vehicles Symposium, IV 2020
CountryUnited States
CityVirtual, Las Vegas
Period10/19/2011/13/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation

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