Consistent Projective Reconstruction from Multiple Views

Martin Urban, Tomáš Pajdla, Václav Hlaváč Abstract Projective reconstruction recovers 3-D points in projective space P3 from their several projections to 2-D images. Applications of projective reconstruction include algorithms for selecting point correspondences, algorithms for camera self-calibration, and algorithms for 3D shape recovery. We introduce a method for the projective reconstruction from n views. The method is based on concatenation of trifocal constraints and relies on linear estimates only. The method is not symmetrical with respect to input data. One of the captured images is selected as a reference image which plays a special role during the computation. The proposed algorithm requires that all the points involved be visible in the reference image. An accuracy and stability of the proposed algorithm with respect to pixel errors were tested. Experimental results are presented too.