Hyon Lim

Seoul National University, Inha University

Papers

Total Citations

102

H-Index

About

Hyon Lim is a researcher whose work lies at the intersection of computer vision, robotics, and real-time localization. His primary research areas include simultaneous localization and mapping (SLAM), 6-DoF pose estimation, and visual odometry, with a strong focus on enabling autonomous navigation for mobile robots. Lim’s most impactful contribution is his work on real-time monocular image-based 6-DoF localization, which has garnered 54 citations. This method continuously computes camera pose estimates from video input by tracking natural features and matching them to a pre-reconstructed scene, offering a practical solution for augmented reality and robot navigation. He also pioneered the use of fiducial markers for single-camera SLAM, introducing an extended Kalman filter-based approach that creates online maps of artificial landmarks—a technique cited 39 times for its robustness in indoor environments. Additionally, Lim explored velocity estimation using RGB-D cameras and optical flow, further advancing mobile robot control. His work is notable for bridging theoretical SLAM algorithms with deployable, real-time systems, making him a key contributor to vision-based autonomous navigation.