Yan Guang
Papers
1
Total Citations
7
H-Index
1
About
Yan Guang is a researcher whose work sits at the intersection of mobile robotics and 3D perception, with a particular focus on solving the challenge of moving object detection in dynamic environments. His most-cited paper, "Moving object detection under dynamic background in 3D range data" (2014, 7 citations), introduces an unsupervised algorithm that extracts profile features to reliably detect moving objects—a critical capability for autonomous systems operating in real-world, cluttered settings. This contribution addresses a long-standing bottleneck in mobile robotics: distinguishing genuine motion from background changes caused by the robot’s own movement or environmental shifts. By proposing a method that works without labeled training data, Yan Guang’s work offers a practical, scalable solution for 3D range data processing. His research sits at the intersection of computer vision, sensor fusion, and autonomous navigation, and his algorithm has been cited by peers working on dynamic scene understanding and robotic perception. Yan Guang’s contributions are particularly notable for their focus on real-world applicability, helping to bridge the gap between theoretical detection methods and the demands of live robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Moving object detection under dynamic background in 3D range data7 citations · 2014