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Sensors 2016, 16(6), 933; doi:10.3390/s16060933

Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera

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Academic Editor: Vittorio M. N. Passaro
Received: 11 March 2016 / Revised: 13 June 2016 / Accepted: 17 June 2016 / Published: 22 June 2016
(This article belongs to the Section Physical Sensors)
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Abstract

LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. View Full-Text
Keywords: extrinsic calibration; indirect correspondence; loop-closing constraint; joint calibration extrinsic calibration; indirect correspondence; loop-closing constraint; joint calibration
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sim, S.; Sock, J.; Kwak, K. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera. Sensors 2016, 16, 933.

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