Papers
1
Total Citations
12
H-Index
1
About
Xiaolan Li’s research centers on 3D object recognition and shape analysis, with a particular focus on CAD models and local shape descriptors. Her most-cited work, “3D Part Identification Based on Local Shape Descriptors” (2008, 12 citations), tackles the critical challenge of identifying and matching 3D parts in complex models—a task essential for fields like computer vision, CAD/CAM, robotics, and multimedia. By developing robust local shape descriptors, Li advanced the ability to recognize objects in cluttered scenes and partial views, laying groundwork for more efficient automated design and manufacturing processes. Her contributions help bridge the gap between raw geometric data and meaningful part identification, enabling progress in applications from molecular biology to industrial robotics. While her citation count reflects a focused, technical audience, the enduring relevance of her work in 3D shape recognition underscores its foundational value. Li’s research continues to influence how engineers and computer scientists approach object recognition in real-world, geometry-rich environments.
Research Focus
Key Achievements
Top Papers
- 13D Part identification based on local shape descriptors12 citations · 2008