Huiqing Pan
Papers
1
Total Citations
37
H-Index
1
About
Huiqing Pan is a computer vision researcher whose work has significantly advanced the field of camera self-calibration and 3D reconstruction. Her most cited paper, "Recovering unknown focal lengths in self-calibration: an essentially linear algorithm and degenerate configurations" (1996, 37 citations), introduced a groundbreaking linear algorithm for recovering focal lengths from stereo image pairs using the fundamental matrix. This work addressed a critical challenge in computer vision: enabling cameras to calibrate themselves automatically without requiring specialized calibration objects. Pan's algorithm elegantly demonstrated that when sufficient corresponding points are available, both the five relative orientation parameters and two unknown focal lengths can be recovered through an essentially linear process. She also provided a thorough analysis of degenerate configurations where this recovery fails, establishing important theoretical foundations for the field. Her contributions have been particularly influential in structure-from-motion and 3D scene reconstruction applications, where automatic calibration is essential. Pan's research continues to be cited by scholars working on camera calibration, multi-view geometry, and autonomous navigation systems, cementing her legacy as a pioneer in practical self-calibration techniques.
Research Focus
Key Achievements
Top Papers
- 1