Wen-Lung Chang
Papers
1
Total Citations
11
H-Index
1
About
Wen-Lung Chang is a researcher whose work lies at the intersection of computer vision, human-robot interaction, and autonomous systems. His most notable contribution is a pioneering approach to real-time human-robot interaction, integrating color and hand gesture recognition for autonomous mobile robots. In his highly cited 2010 paper, Chang tackled the critical challenge of robust gesture recognition under varying lighting conditions, proposing a method that combines color and shape cues to improve reliability. This work, which has garnered 11 citations, addresses two fundamental problems: color variation under changing illumination and the need for efficient, real-time processing. Chang’s research has practical implications for developing more intuitive and responsive robotic systems, enabling seamless communication between humans and machines. His contributions are particularly valuable in fields such as assistive robotics, industrial automation, and autonomous navigation, where reliable gesture recognition is essential. By advancing the integration of visual cues, Chang has helped pave the way for more adaptive and user-friendly robotic interfaces, making his work a key reference for researchers exploring vision-based human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1