Jae Yeon Lee

Electronics and Telecommunications Research Institute

Papers

Total Citations

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About

Jae Yeon Lee is a researcher whose work lies at the intersection of computer vision, robotics, and human-robot interaction. His primary research areas include moving object detection and tracking, object recognition and pose estimation, and motion analysis for robotic systems. Lee’s most influential contribution is his 2005 paper on detecting and tracking moving objects using an active camera mounted on a mobile robot, which has garnered 28 citations. In this work, he pioneered a method to analyze and compensate for camera motion by comparing edge features across consecutive frames, enabling robust detection of moving objects through frame differencing. He further advanced industrial robotics with his 2013 study on object recognition methods for intelligent robots, integrating 2D and 3D vision sensors for automated packaging tasks. Lee also developed innovative feature-based recognition techniques, such as KLT-D and SURF-D, to achieve rotation and position invariance in object pose estimation. His 2005 exploration of motion analysis for human-robot interaction, though less cited, laid groundwork for understanding how robots can interpret human motion in dynamic environments. Collectively, Lee’s work has shaped practical applications in automated factories and mobile robotics, demonstrating lasting impact in vision-guided systems.