George Terzakis

University of Portsmouth, University of Plymouth

Papers

Total Citations

H-Index

About

George Terzakis is a researcher whose work lies at the intersection of computer vision and robotics, with a sharp focus on the fundamental problem of orientation estimation. His most impactful contribution, the 2018 paper "Efficient Absolute Orientation Revisited," introduces a novel algorithm for determining the similarity transformation between corresponding 3D point sets—a core task in applications like 3D reconstruction and sensor fusion. Building on the Fast Optimal Attitude Matrix (FOAM) method, this work has garnered 12 citations for its practical efficiency. Terzakis also made a significant theoretical contribution with his 2013 paper "On quaternion based parameterization of orientation in computer vision and robotics," which provides a comprehensive and accessible guide to using quaternions for iterative optimization in orientation problems. With 6 citations, this work serves as a valuable resource for practitioners seeking to avoid common pitfalls in parameterization. Together, these papers establish Terzakis as a key figure in advancing both the theory and practical algorithms for absolute orientation, offering tools that are directly applicable to modern robotic perception and vision systems.