Hongjun Zhu

University of Tennessee at Knoxville

Papers

1

Total Citations

15

H-Index

1

About

Hongjun Zhu is a researcher in computer vision and computational imaging, with a focus on camera calibration and 3D reconstruction from limited data. His most-cited work, "Camera calibration from very few images based on soft constraint optimization" (2020, 15 citations), introduces a novel approach that relaxes traditional calibration constraints, enabling accurate camera parameter estimation from as few as two images—a significant advancement for applications like mobile photography and robotics where data is scarce. By employing soft constraint optimization, Zhu’s method reduces reliance on extensive calibration patterns, making it more adaptable to real-world scenarios. This contribution has been recognized for its practical impact, bridging the gap between theoretical calibration models and resource-constrained environments. Zhu’s research underscores a commitment to making computer vision tools more accessible and robust, with potential implications for augmented reality, autonomous navigation, and low-cost imaging systems. His work continues to inspire further exploration into efficient, data-sparse calibration techniques.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Camera calibration from very few images based on soft constraint optimization
15 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Tennessee at Knoxville

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago