PeRL STUDIES AUTONOMOUS NAVIGATION & MAPPING FOR MOBILE ROBOTS IN A PRIORI UNKNOWN ENVIRONMENTS.
Here are the softwares and datasets that we have released to the public.
Extrinsic Calibration of a 3D Lidar and Camera
This software is an implementation of our mutual information (MI) based algorithm for automatic extrinsic calibration of a 3D laser scanner and optical camera system. By using MI as the registration criterion, our method is able to work in situ without the need for any specific calibration targets, which makes it practical for in-field calibration. More details are given in the paper "Automatic Targetless Extrinsic Calibration of a 3D Lidar and Camera by Maximizing Mutual Information".
A simple animation to show the proposed algorithm. The top panel shows the projection of the 3D points onto the camera image as the yaw changes. The bottom panel (right) shows the correlation coefficient of the intensity and reflectivity values as a function of the changing yaw angle. The bottom panel (left) shows the the joint histogram of the reflectivity and the intensity values when calculated at these yaw angles. Note that under the correct yaw angle the correlation coefficient is maximized and the joint histogram is least dispersed. Please cite paper  below if you use it.
Please send bug reports to Gaurav Pandey: <email@example.com>