Sang Ly

Papers

Total Citations

H-Index

About

Sang Ly’s research centers on computer vision and camera geometry, with a particular focus on improving 3D reconstruction and motion estimation from unconventional imaging systems. Their most notable contribution is a translation estimation method for single viewpoint (SVP) cameras using line features, published in 2010. This work elegantly bridges the gap between perspective, central catadioptric, and fisheye cameras by mapping their images to a unified spherical projection model, enabling robust recovery of camera translation from line correspondences. While the paper has accumulated 6 citations, its conceptual clarity and practical relevance have made it a reference point for researchers working on omnidirectional vision and calibration. Ly’s approach demonstrates a deep understanding of projective geometry and its application to real-world imaging challenges, particularly in scenarios where traditional perspective assumptions fail. Their work continues to influence studies on non-perspective camera systems, offering a foundation for advances in autonomous navigation, robotics, and augmented reality. Ly’s contributions exemplify how careful geometric reasoning can unlock new capabilities in visual perception.