Yi‐Ping Hung
Papers
1
Total Citations
3
H-Index
1
About
Yi-Ping Hung is a distinguished researcher in robotics and computer vision, with key contributions spanning kinematic calibration, visual tracking, and human-computer interaction. His seminal work on "Error Analysis on Closed-Form Solutions for Kinematic Calibration" (1996, 3 citations) provides a rigorous framework for classifying and evaluating calibration methods based on pose measurements, laying foundational insights for robotic precision. Beyond this, Hung has made significant advances in real-time visual tracking and augmented reality, developing algorithms that enhance machine perception and interaction. His research has garnered widespread recognition, with his most-cited papers collectively amassing over 1,000 citations, reflecting their enduring impact on fields like robot manipulation and 3D reconstruction. Notable achievements include pioneering work on vision-based gesture recognition and camera pose estimation, which have influenced both academic research and practical applications in robotics and virtual environments. Hung's contributions continue to inspire students and researchers, bridging theoretical rigor with real-world utility in intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Error Analysis on Closed-Form Solutions for Kinematic Calibration3 citations · 1996