Papers
1
Total Citations
2
H-Index
1
About
Nan Gao is a researcher whose work lies at the intersection of computer vision, robotics, and visual sensing, with a particular focus on advancing pose estimation and motion analysis. Her most-cited paper, "Position and orientation determination using quadric fitting optimization for object’s motion analyzing" (2025), addresses a fundamental challenge in the field: accurately determining the position and orientation of moving objects from images. This work introduces a novel quadric fitting optimization approach that overcomes the limitations of traditional pose estimation methods, which often struggle in complex, real-world scenarios. By improving robustness and precision, Gao’s research has direct implications for applications in robotics, augmented reality, and autonomous systems. While her career is still in its early stages, with 2 citations to date, her contribution represents a meaningful step forward in visual sensing technology. Gao’s work is particularly notable for its potential to enhance object tracking and motion analysis in dynamic environments, making her a promising voice in the ongoing effort to bridge the gap between theoretical computer vision and practical, real-time deployment.
Research Focus
Key Achievements
Top Papers
- 1