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About

Jan Heller is a leading researcher in robotic vision and sensor calibration, with a primary focus on hand-eye and world-base calibration—critical problems that enable robots to accurately relate camera measurements to their own coordinate systems. His most influential work, "Structure-from-motion based hand-eye calibration using L∞ minimization" (2011, 46 citations), introduced a groundbreaking method that eliminates the need for a calibration target, recovering camera poses up to scale through Structure-from-Motion. This innovation is particularly valuable for applications where traditional calibration targets are impractical. Heller further advanced the field with his "Hand-Eye Calibration without Hand Orientation Measurement Using Minimal Solution" (2013) and "Hand-eye and robot-world calibration by global polynomial optimization" (2014, 7 citations), which provided globally optimal solutions using polynomial optimization techniques. His later work on world-base calibration (2014, 4 citations) extended these methods to robotic manipulator systems. With over 70 total citations across his key papers, Heller's contributions have significantly improved the accuracy and practicality of sensor-guided robotics, making him a notable figure in the intersection of computer vision and robotics.