Reconstruction of projective and metric cameras for image triplets
Andrey Khropov, A. V. Shokurov, Victor Lempitskiy, Д. В. Иванов · 2004
One of the most important parts of 3D computer vision systems is reconstruction of cameras. In this paper we describe our approach to the reconstruction of parameters of the three uncalibrated cameras using information from the three projections of the static scene. We match distinct features of the scene (such as corner points and straight line segments) and robustly sift out outlier matches using RANSAC techniques. Then the optimal trifocal tensor is built using an iterative algorithm which uses inlier matches. This trifocal tensor is used to reconstruct projective cameras. Finally these cameras may be transformed to metric if certain assumptions are presumed. The algorithm pipeline is fully automatic.