Lab Meeting October 13 (Andi) Extrinsic Laser Scanner / Camera calibration

I will summarize three papers with different approaches for Laser/Camera calibration.

[1] An Algorithm for Extrinsic Parameters Calibration of a Camera and a Laser Range Finder Using Line Features
[2] An efficient extrinsic calibration of a multiple laser scanners and cameras’ sensor system on a mobile platform
[3] Extrinsic calibration of a camera and laser range finder (improves camera calibration)

Abstracts:
[1]This paper presents an effective algorithm for calibrating the extrinsic parameters between a camera and a laser range finder whose trace is invisible. On the basis of an analysis of three possible features, we propose to design a right-angled triangular checkerboard and to employ the invisible intersection points of the laser range finder’s slice plane with the edges of the checkerboard to set up the constraints equations. The extrinsic parameters are then calibrated by minimizing the algebraic errors between the measured intersections points and their corresponding projections on the image plane of the camera....
[2] ...In this research, we present a practical method for extrinsic calibration of multiple laser scanners and video cameras that are mounted on a vehicle platform. Refering to a fiducial coordinate system on vehicle platform, a constraint between the data of a laser scanner and of a video camera is established. It is solved in an iterative way to find a best solution from the laser scanner and from the video camera to the fiducial coordinate system. On the other hand, all laser scanners and video cameras are calibrated for each laser scanner and video camera pair that has common in feature points in a sequential way....
[3] We describe theoretical and experimental results for the extrinsic calibration of sensor platform consisting of a camera and a 2D laser range finder. The calibration is based on observing a planar checkerboard pattern and solving for constraints between the “views” of a planar checkerboard calibration pattern from a camera and laser range finder. We give a direct solution that minimizes an algebraic error from this constraint, and subsequent nonlinear refinement minimizes a re-projection error....