Yeung Sam Hung
Papers
2
Total Citations
4
H-Index
2
About
Yeung Sam Hung is a researcher whose work lies at the intersection of computer vision and robotics, with a particular focus on visual servoing and 3D object tracking. His major contributions include developing robust methods for detecting and tracking multiple moving objects using uncalibrated monocular cameras, a critical capability for autonomous systems operating in dynamic environments. In his 2009 paper on this topic, Hung introduced novel 3D feature-based approaches that enhance tracking stability without requiring prior camera calibration. He has also made significant strides in understanding and mitigating image measurement errors in visual servoing, quantifying how these errors induce positioning inaccuracies in robotic control systems. While his citation counts—2 each for his most-cited works—reflect a niche but specialized impact, his research addresses fundamental challenges in real-world robotic perception. Hung’s work is particularly notable for its practical emphasis on uncalibrated systems, which reduces the need for expensive calibration equipment and makes his methods more accessible for deployment in unstructured environments. His contributions continue to inform the development of more resilient and adaptable vision-based robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2