Zihui Xiong

University of Alberta

Papers

1

Total Citations

11

H-Index

1

About

Zihui Xiong is a researcher in computer vision and 3D reconstruction, with a focus on efficient geometric algorithms for omni-directional imaging. His most notable contribution is the development of a 2-point algorithm for reconstructing 3D horizontal lines from a single omni-directional image, published in 2010. This work addresses a fundamental challenge in scene understanding—extracting depth and structure from wide-angle views with minimal input data. By reducing the required correspondences to just two points, Xiong’s method enables faster and more robust reconstruction in real-world environments, such as autonomous navigation and augmented reality. Although his most-cited paper has garnered 11 citations, its impact lies in its theoretical elegance and practical utility for resource-constrained systems. Xiong’s research bridges the gap between theoretical geometry and applied vision systems, offering solutions that are both mathematically rigorous and computationally efficient. His work continues to inspire advancements in single-image 3D reconstruction, particularly for omni-directional and fisheye cameras, making him a valuable contributor to the field of geometric computer vision.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A 2-point algorithm for 3D reconstruction of horizontal lines from a single omni-directional image
11 citations · 2010
📈 Most Prolific Year: 2010 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Alberta

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago