Fundamental Matrix Computing Based on 3D Metrical Distance

To reconstruct point geometry from multiple images, computation of the fundamental matrix is always necessary. With a new optimization criterion, i.e., re-projective 3D metric geometric distance rather than projective space under RANSAC (Random Sample And Consensus) framework, our method can reveal quality visually through reconstruction. The projection error points to corresponding image pixel coordinates in space. reasonable visual figures reconstructed scenes are shown but only some numerical result were compared, as standard practice. This criterion lead better reconstruction especially Our experiments validate and criterion.