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Paper WeA105.4

Carrera, Gerardo (Imperial College London), Angeli, Adrien (Imperial College London), Davison, Andrew J (Imperial College London)

SLAM-Based Automatic Extrinsic Calibration of a Multi-Camera Rig

Scheduled for presentation during the Regular Sessions "SLAM I" (WeA105), Wednesday, May 11, 2011, 09:05−09:20, Room 3G

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on December 10, 2019

Keywords Computer Vision for Robotics and Automation, SLAM, Omnidirectional Vision

Abstract

Here we present a general method for fully automatic extrinsic auto-calibration of a fixed multi camera rig, with no requirement for calibration patterns or other infrastructure, which works even in the case where the cameras have completely non-overlapping views. The robot is placed in a natural environment and makes a set of programmed movements including a full horizontal rotation and captures a synchronized image sequence from each camera. These sequences are processed individually with a monocular visual SLAM algorithm. The resulting maps are matched and fused robustly based on corresponding invariant features, and then all estimates are optimised full joint bundle adjustment, where we constrain the relative poses of the cameras to be fixed. We present results showing accurate performance of the method for various camera configurations.

 

 

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