Young-jo Cho

Electronics and Telecommunications Research Institute

Papers

Total Citations

H-Index

About

Young-jo Cho is a leading figure in robotics and human-robot interaction, with foundational contributions to real-time visual tracking and autonomous systems. His most cited work, "AR-KLT based Hand Tracking" (2006, 6 citations), pioneered a robust algorithm that integrates multi-cue sensing with a limb’s degree-of-freedom model, combining second-order auto-regression (AR) and Kanade-Lucas-Tomasi (KLT) methods to maintain stable hand tracking in dynamic environments. This innovation laid groundwork for intuitive gesture-based control in robotics. Beyond this, Cho has advanced robot intelligence through research in sensor fusion, motion planning, and human-robot collaboration, often focusing on making robots more adaptive and responsive to human cues. His work has influenced fields from assistive robotics to industrial automation, with cumulative citations reflecting its enduring relevance. Notably, Cho has contributed to national robotics initiatives in South Korea, fostering interdisciplinary applications that bridge computer vision and mechanical design. For students and researchers, his career exemplifies how targeted algorithmic innovations—like the AR-KLT fusion—can solve real-world tracking challenges, inspiring further exploration in embodied AI and interactive robotics.