Yong-Cheol Lee
Papers
1
Total Citations
9
H-Index
1
About
Yong-Cheol Lee is a robotics researcher whose work focuses on computer vision and autonomous navigation, particularly in dynamic environments. His key research areas include omnidirectional vision systems, moving object detection, and mobile robot perception. Lee’s major contribution lies in addressing the complex challenge of detecting moving objects from a moving platform—a problem where both the background and the target move independently due to the robot’s own motion (ego-motion). His 2012 paper on moving object detection in omnidirectional vision-based mobile robots, which has garnered 9 citations, proposes a method to isolate object movement by compensating for background changes caused by the robot’s motion. This work is notable for advancing the reliability of perception in autonomous systems, enabling safer navigation in cluttered, real-world settings. Lee’s research has practical implications for service robots, autonomous vehicles, and surveillance systems. His achievements include developing algorithms that enhance the robustness of visual tracking in non-static environments, laying groundwork for future innovations in mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1Moving object detection in omnidirectional vision-based mobile robot9 citations · 2012