Woo Keun Jo

Papers

Total Citations

H-Index

About

Woo Keun Jo is a researcher whose work lies at the intersection of computer vision and robotics, with a particular focus on real-time human-robot interaction. His most cited contribution, "A study on face tracking in real-time for robot" (2008), proposed an innovative face detection and tracking system designed for humanoid robots. By integrating skin color modeling with deformable ellipse matching on an embedded computing platform, Jo enabled robots to observe and recognize unknown individuals in dynamic environments—a foundational step toward more responsive and socially aware machines. While his work has garnered over 4 citations, its true impact lies in its practical application to real-world robotic systems, bridging the gap between algorithmic efficiency and hardware constraints. Jo’s research addresses a critical challenge in robotics: enabling machines to perceive and interact with humans naturally in uncontrolled settings. His contributions continue to inform developments in autonomous systems, particularly in areas requiring robust, real-time visual tracking. For students and researchers exploring human-robot collaboration, Jo’s work offers a clear example of how vision-based techniques can be tailored for embedded, performance-limited platforms.