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PERCEPTION

Infrared stereo calibration for unmanned ground vehicle navigation

Josh Harguess, Shawn Strange

Year
2014
Citations
10

Abstract

The problem of calibrating two color cameras as a stereo pair has been heavily researched and many off-the-shelf software packages, such as Robot Operating System and OpenCV, include calibration routines that work in most cases. However, the problem of calibrating two infrared (IR) cameras for the purposes of sensor fusion and point could generation is relatively new and many challenges exist. We present a comparison of color camera and IR camera stereo calibration using data from an unmanned ground vehicle. There are two main challenges in IR stereo calibration; the calibration board (material, design, etc.) and the accuracy of calibration pattern detection. We present our analysis of these challenges along with our IR stereo calibration methodology. Finally, we present our results both visually and analytically with computed reprojection errors.

Keywords

Computer visionArtificial intelligenceCalibrationComputer scienceReprojection errorStereo cameraCamera resectioningUnmanned ground vehicleStereo camerasRobot

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