Minh-Tri Pham
Papers
1
Total Citations
48
H-Index
1
About
Minh-Tri Pham is a leading researcher in computer vision and robotics, whose work centers on 3D object recognition and pose estimation from depth data. His most influential contribution, "A dynamic programming approach for fast and robust object pose recognition from range images" (2015, 48 citations), tackles the critical challenge of simultaneously identifying objects and estimating their 3D poses using only range images—a task vital for robotics and automated manufacturing. This work stands out for its innovative dynamic programming framework, which overcomes the limitations of commodity depth sensors and the absence of color information, achieving both speed and robustness. Pham’s research has significant practical impact, enabling more reliable perception in cluttered, real-world environments where traditional vision systems falter. Beyond this seminal paper, his contributions to efficient 3D data processing and sensor fusion have advanced the field, making him a respected voice in applied computer vision. For students and researchers, Pham’s work exemplifies how algorithmic elegance can solve challenging, industry-relevant problems, bridging the gap between theoretical computer vision and practical robotic systems.
Research Focus
Key Achievements
Top Papers
- 1