Rong Dai

Chinese University of Hong Kong

Papers

1

Total Citations

44

H-Index

1

About

Rong Dai is a leading researcher in three-dimensional computer vision, with a particular focus on the challenging problem of reconstructing transparent objects. Their work addresses a critical gap in robotics and industrial automation, where traditional 3D scanning methods fail due to the refractive and reflective properties of glass, plastic, and other see-through materials. Dai’s most influential contribution is the development of the LTFtF (Laser Triangulation with Frequency-domain Filtering) method, which combines laser scanning with stereo matching to accurately recover the 3D surfaces of transparent objects. This pioneering approach, detailed in their 2021 paper that has garnered 44 citations, offers a practical solution for quality inspection and robotic manipulation in manufacturing environments. By overcoming the limitations of conventional depth sensors, Dai’s research enables more robust and reliable automation systems. Their work stands at the intersection of optics, signal processing, and computer vision, making significant strides toward bridging the gap between laboratory theory and real-world industrial application.

Research Focus

Key Achievements

1
H-Index
1
Papers
44
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
3D Surface reconstruction of transparent objects using laser scanning with LTFtF method
44 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Chinese University of Hong Kong

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago