Qiuhong Ke

Carnegie Mellon University

Papers

1

Total Citations

34

H-Index

1

About

Qiuhong Ke is a leading researcher in computer vision and autonomous systems, with a particular focus on state estimation, structure from motion (SFM), and Kalman filtering techniques for aerial platforms. Her most-cited work, "Vision-Based Kalman Filtering for Aircraft State Estimation and Structure from Motion" (2005, 34 citations), provides a critical synthesis of feature point tracking, SFM algorithms, and Kalman filtering tailored specifically to the challenges of aircraft state estimation. This paper stands out for its practical emphasis on methods well-suited to real-time, dynamic aerial environments, bridging theoretical computer vision with applied aerospace engineering. Ke’s contributions have advanced the integration of vision-based sensors into autonomous navigation systems, enabling more robust and accurate state estimation for unmanned aerial vehicles. Her work is particularly notable for its clarity in distilling complex algorithms into actionable frameworks for aircraft applications. With a citation count reflecting sustained interest from both the computer vision and robotics communities, Ke’s research continues to influence the development of reliable, vision-driven autonomy in challenging operational conditions.

Research Focus

Key Achievements

1
H-Index
1
Papers
34
Total Citations
34
Avg Citations/Paper
🏆 Most Cited Paper
Vision-Based Kalman Filtering for Aircraft State Estimation and Structure from Motion
34 citations · 2005
📈 Most Prolific Year: 2005 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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