The Chow Form of the Essential Variety in Computer Vision
arXiv:1604.04372v222 citations
AI Analysis
This work provides a theoretical tool for computer vision researchers working on 3D reconstruction and motion estimation, though it appears incremental as it builds on known mathematical frameworks.
The authors derived the Chow form of the essential variety in computer vision, a mathematical representation used to describe epipolar geometry between two images, and demonstrated through numerical experiments that their formula can detect noisy point correspondences.
The Chow form of the essential variety in computer vision is calculated. Our derivation uses secant varieties, Ulrich sheaves and representation theory. Numerical experiments show that our formula can detect noisy point correspondences between two images.