Papers
2
Total Citations
14
H-Index
2
About
Laishui Zhou’s research lies at the intersection of computer graphics, geometric modeling, and 3D vision, with a particular focus on robust scene reconstruction and surface curve design. In their highly cited 2021 work on RGB-D reconstruction, Zhou introduced a method that leverages line feature constraints to achieve accurate camera tracking and scene reconstruction—even in geometrically featureless environments or under challenging lighting conditions. This contribution addresses a critical bottleneck in consumer-level 3D scanning, enabling more reliable performance for robotics and vision applications. Prior to this, Zhou developed a novel approach for constructing G¹ continuous curves on free-form surfaces using normal projection, a technique that ensures smooth interpolation of points with specified tangent directions on implicit or parametric surfaces. Each of these papers has garnered 7 citations, reflecting their targeted impact on advancing practical geometric computation. Zhou’s work demonstrates a sustained commitment to solving real-world problems in 3D reconstruction and surface modeling, bridging the gap between theoretical geometry and applied robotics.
Research Focus
Key Achievements
Top Papers
- 1Robust and Accurate RGB-D Reconstruction With Line Feature Constraints7 citations · 2021
- 2