Automatic relative orientation of large scale imagery over urban areas using Modified Iterated Hough Transform

The automation of relative orientation (RO) has been the major focus of the photogrammetric research community in the last decade. Despite the reported progress, there is no reliable (robust) approach that can perform automatic relative orientation (ARO) using large-scale imagery over urban areas. A reliable and general method for solving matching problems in various photogrammetric activities has been developed at The Ohio State University, This approach has been used to solve single photo resection using free-form linear features, surface matching and relative orientation. The approach estimates the parameters of a mathematical model relating the entities of two datasets when the correspondence of the involved entities is unknown, When applied to relative orientation, the coplanarity model is used to relate extracted edge pixels and/or feature points from a stereo-pair. In its execution, the relative orientation parameters are solved sequentially, using the coplanarity model to evaluate all possible pairings of the input primitives and choosing the most probable solution. As a result of this technique, the matched entities that correspond to the parameter solution are implicitly determined. Experiments using real data conclude that this is a robust method for relative orientation for both urban and rural scenes. (C) 2001 Elsevier Science B.V. All rights reserved.