Experimental Evaluation of 3D-LIDAR Camera Extrinsic Calibration

TL;DR

This paper compares three target-based 3D-LIDAR camera calibration algorithms through extensive experiments, analyzing their robustness, accuracy, and practical considerations for different sensor configurations.

Contribution

It provides a comprehensive experimental evaluation and comparison of three calibration algorithms, including insights into their robustness and practical deployment.

Findings

All algorithms' robustness varies with initialization and noise.

Calibration accuracy is affected by sensor noise and data collection methods.

Recommendations are provided for choosing the appropriate calibration method.

Abstract

In this paper we perform an experimental comparison of three different target based 3D-LIDAR camera calibration algorithms. We briefly elucidate the mathematical background behind each method and provide insights into practical aspects like ease of data collection for all of them. We extensively evaluate these algorithms on a sensor suite which consists multiple cameras and LIDARs by assessing their robustness to random initialization and by using metrics like Mean Line Re-projection Error (MLRE) and Factory Stereo Calibration Error. We also show the effect of noisy sensor on the calibration result from all the algorithms and conclude with a note on which calibration algorithm should be used under what circumstances.