Changyong Yoon

Papers

Total Citations

H-Index

About

Changyong Yoon is a researcher in computer vision and human-robot interaction, with a focus on robust hand gesture recognition—a critical enabler for intuitive control of smart devices, from smartphones to smart TVs. His most-cited work, "Part-based Hand Detection Using HOG" (2013, 7 citations), addresses a core challenge in the field: detecting hands reliably under varying poses, complex backgrounds, and changing lighting conditions. Yoon’s key contribution is a novel algorithm that reduces false detections by first locating the head and shoulders to constrain the hand search region, then applying skin-color filtering to refine detection. This part-based, context-aware approach improves accuracy in indoor pointing-gesture recognition, a vital component for seamless human-robot interaction. While his citation count reflects a focused, early-stage impact, Yoon’s work lays practical groundwork for more robust, real-world gesture interfaces. His research underscores the importance of integrating geometric and color cues to overcome the inherent variability of hand shapes, offering a pragmatic solution for engineers developing responsive, user-friendly robotic and smart systems.