Jeongho Shin
Papers
2
Total Citations
121
H-Index
2
About
Jeongho Shin is a researcher whose work bridges computer vision and robotics, with key contributions in real-time object tracking and mechanical design. His most cited paper, "Optical flow-based real-time object tracking using non-prior training active feature model" (2005, 88 citations), introduces a novel method that combines optical flow with an active feature model, enabling robust tracking without prior training—a significant advancement for dynamic environments. This work has been foundational for subsequent research in autonomous systems and surveillance. In the realm of robotics, Shin’s 2013 paper on "Design of thin plate-type speed reducers using balls for robots" (33 citations) presents an innovative mechanical solution for compact, efficient motion control, directly impacting the development of lightweight robotic joints. His contributions demonstrate a unique ability to integrate algorithmic and hardware innovations, addressing both perception and actuation challenges. With a citation profile reflecting sustained influence, Shin’s research continues to inspire advances in real-time vision systems and robotic mechanics, making him a notable figure in applied engineering.
Research Focus
Key Achievements
Top Papers
- 1
- 2Design of thin plate-type speed reducers using balls for robots33 citations · 2013