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AUTHOR ====== Gaurav Pandey. email: email@example.com Redistribution and use in source and binary forms, with or without modification, are permitted under the GNU Lesses General Public License (see LICENSE) MODIFIED BY (2017) =========== Andreas L. Flaten email: firstname.lastname@example.org ABOUT ===== This is a reference implementation of mutual information (MI) based algorithm for automatic extrinsic calibration of a 3D laser scanner and optical camera system. You can find specific details in the original paper: "Automatic Targetless Extrinsic Calibration of a 3D Lidar and Camera by Maximizing Mutual Information." in AAAI, special track on robotics, July 2012, Toronto, Canada. LIBRARIES USED ============== This version is implemented with the help of some external code: 1) GSL : http://www.gnu.org/software/gsl/ 2) OpenCV 2.3.1 : http://opencv.willowgarage.com/wiki/ (Lower versions of opencv might not work) 3) Glib : http://developer.gnome.org/glib/stable/ 4) CMake : http://www.cmake.org/ COMPILATION INSTRUCTIONS ======================== 1. Go to build/ and run "cmake ../". It will generate the required make files. 2. Run "make". It will generate the binary "mi-extrinsic-calib" in the directory bin/ USAGE INSTRUCTIONS ================== 1. Go to config/ and update the default config file (if needed). The config file contains all the inputs required by the algorithm. This config file contains intrinsic parameters of a laser scanner and an omnidirectional camera used for developing this algorithm. Sample data from this laser scanner and the omnidirectional camera is provided in bin/data/. 2. Go to bin/ and run "./mi-extrinsic-calib". If you do not provide any argument then it will use the default config file "config/master.cfg" that corresponds to a Ladybug3 omni- directional camera. A sample config file for a monocular camera setup is given as "config/monocular-cam.cfg" 3. At the end of the program two output files are created in bin/. "calib_param.txt" stores the estimated calibration parameters. "calib_cov.txt" stores the estimated 6x6 covariance matrix.
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