Farhad Dalirani, May 2023--April 2024, "A Target-Based and A Targetless Extrinsic Calibration Methods for Thermal Camera and 3D LiDAR", Computer Science Department, Faculty of Science, University of Western Ontario, Canada
M.Sc. Thesis Abstract
This thesis introduces two novel methods for the extrinsic calibration of a thermal camera and a 3D LiDAR sensor, which are crucial for seamless data integration. The first method employs a distinctive calibration target, leveraging lines and plane equations correspondence in both modalities for a single pose, and incorporating more poses by matching the target's edges. It achieves reliable results, even with just one pose yielding 10.82% translation and $0.51$-degree rotation errors. This outperforms alternative methods, which require eight pairs for similar results. The second method eliminates the need for a dedicated target. Instead, by collecting data during the sensor setup movement in environment and using a novel evolutionary algorithm optimizes a loss that measures alignment of humans in both modalities. This approach results in a 4.43% loss improvement compared to extrinsic parameters obtained by target-based methods. These methods save calibration time, reduce costs, and make sensor integration more accessible.