Pierre Greisen

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About

Pierre Greisen is a leading researcher in computer vision and robotics, with a core focus on real-time motion estimation for autonomous systems. His most influential work, "Real-time velocity estimation based on optical flow and disparity matching" (2012), has garnered 53 citations and addresses a critical challenge in micro aerial vehicle (MAV) navigation: the need for high-update-rate metric velocity data without external references. Greisen’s key contribution lies in elegantly fusing optical flow measurements with disparity matching to derive scale-aware velocity estimates, enabling robust navigation control loops for mobile robots. This approach eliminates reliance on GPS or external beacons, making it particularly valuable for indoor and GPS-denied environments. His research has significantly advanced the field of visual odometry, providing a computationally efficient solution that balances accuracy and real-time performance—a crucial trade-off for lightweight MAVs. Greisen’s work continues to influence modern autonomous navigation systems, and his 2012 paper remains a foundational reference for researchers developing vision-based control for agile robots.