Papers
2
Total Citations
3
H-Index
1
About
Du Trinh Ngoc is a rising researcher in the field of computer vision and robotics, with a focused expertise in monocular 3D object localization for industrial applications. His primary research addresses the critical challenge of enabling robot vision systems to accurately perceive and interact with objects in three-dimensional space using only a single camera. Ngoc’s major contribution lies in developing novel, cost-effective methods that blend deep learning—specifically object detection and pose estimation—with post-image processing algorithms to localize isometric flat objects. His work, detailed in papers like "M-Calib: A Monocular 3D Object Localization using 2D Estimates for Industrial Robot Vision System" (2024) and its follow-up (2025), proposes a pipeline that leverages 2D image estimates to infer precise 3D positions, a significant step toward affordable and efficient automation. While his citation counts are currently modest (2 and 1), his research is at the forefront of a rapidly growing field, offering practical solutions for real-world manufacturing and robotics. Ngoc’s work is particularly notable for its direct industrial applicability, promising to bridge the gap between advanced computer vision theory and tangible robotic systems.
Research Focus
Key Achievements
Top Papers
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