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In this paper, we propose a new algorithm to establish the data association between a camera and a 2-D LIght Detection And Ranging sensor (LIDAR). In contrast to the previous works, where data association is established by calibrating the intrinsic parameters of the camera and the extrinsic parameters of the camera and the LIDAR, we formulate the map between laser points and pixels as a 2-D homography. The line-point correspondence is employed to construct geometric constraint on the homography matrix. This enables checkerboard to be not essential and any object with straight boundary can be an effective target. The calculation of the 2-D homography matrix consists of a linear least-squares solution of a homogeneous system followed by a nonlinear minimization of the geometric error in the image plane. Since the measurement quality impacts on the accuracy of the result, we investigate the equivalent constraint and show that placing the calibration target nearby the 2-D LIDAR will provide sufficient constraints to calculate the 2-D homography matrix. Simulation and experimental results validate that the proposed algorithm is robust and accurate. Compared with the previous works, which require two calibration processes and special calibration targets such as checkerboard, our method is more flexible and easier to perform.


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A New Algorithm for the Establishing Data Association Between a Camera and a 2-D LIDAR

Show Author's information Lipu ZhouZhidong Deng( )
State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.

Abstract

In this paper, we propose a new algorithm to establish the data association between a camera and a 2-D LIght Detection And Ranging sensor (LIDAR). In contrast to the previous works, where data association is established by calibrating the intrinsic parameters of the camera and the extrinsic parameters of the camera and the LIDAR, we formulate the map between laser points and pixels as a 2-D homography. The line-point correspondence is employed to construct geometric constraint on the homography matrix. This enables checkerboard to be not essential and any object with straight boundary can be an effective target. The calculation of the 2-D homography matrix consists of a linear least-squares solution of a homogeneous system followed by a nonlinear minimization of the geometric error in the image plane. Since the measurement quality impacts on the accuracy of the result, we investigate the equivalent constraint and show that placing the calibration target nearby the 2-D LIDAR will provide sufficient constraints to calculate the 2-D homography matrix. Simulation and experimental results validate that the proposed algorithm is robust and accurate. Compared with the previous works, which require two calibration processes and special calibration targets such as checkerboard, our method is more flexible and easier to perform.

Keywords: sensor fusion, 2-D homography, extrinsic calibration, camera calibration

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Publication history

Received: 28 April 2014
Accepted: 05 May 2014
Published: 18 June 2014
Issue date: June 2014

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© The author(s) 2014

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Nos. 90820305 and 60775040) and the National High-Tech Research and Development (863) Program of China (No. 2012AA041402).

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