Minimal problems in Computer Vision

Minimal problems in computer vision arise when computing geometrical models from image data.
They often lead to solving systems of algebraic equations.

This page provides links to publications, software, data, and evaluation of minimal problems.

NEW: ICCV 2009

Bujnak M., Kukelova Z., and Pajdla T. 3D reconstruction from image collections with a single known focal length. ICCV 2009, Kyoto, Japan, September 29 - October 2, 2009. [pdf]
CODE:
6-point relative pose problem for one calibrated and one up to focal length calibrated camera

Minimal problems:

3-pt absolute pose problem (P3P)
4-pt absolute pose problem with unknown focal length (P4Pf)
4-pt absolute pose problem with unknown focal length and radial distortion (P4Pfr)
5-pt relative pose problem
6-point relative pose problem with unknown focal length
6-point relative pose problem for one calibrated and one up to focal length calibrated camera
6-point generalized camera problem
2-point panorama stitching problem with one unknown focal lenth
3-point panorama stitching problem with two different unknown focal lenths
3-point panorama stitching problem with one unknown focal lenth and radial distortion
6-point relative pose problem with radial distortion
8-point "uncalibrated" relative pose problem with radial distortion
9-point "uncalibrated" relative pose problem with different radial distortions
3-view triangulation
9-pt catadioptric problem

Tomas Pajdla, Zuzana Kukelova, Martin Bujnak. Maintained by Zuzana Kukelova, 22 October 2009