TitleFactorization of Correspondence and Camera Error for Unconstrained Dense Correspondence Applications (In Proceedings)
in5th International Symposium on Visual Computing
Author(s) Daniel Knoblauch, Mauricio Hess-Flores, Mark A. Duchaineau, Falko Kuester
Year 2009
LocationLas Vegas, NV
DateNovember 30 - December 2, 2009
Abstract A correspondence and camera error analysis for dense correspondence applications such as structure from motion is introduced. This provides error introspection, opening up the possibility of adaptively and progressively applying more expensive correspondence and camera parameter estimation methods to reduce these errors. The presented algorithm evaluates the given correspondences and camera parameters based on an error generated through simple triangulation. This triangulation is based on the given dense, non-epipolar constraint, correspondences and estimated camera parameters. This provides an error map without requiring any information about the perfect solution or making assumptions about the scene. The resulting error is a combination of correspondence and camera parameter errors. An simple, fast low/high pass filter error factorization is introduced, allowing for the separation of correspondence error and camera error. Further analysis of the resulting error maps is applied to allow efficient iterative improvement of correspondences and cameras.