Development of method to automatically select passpoints for close range photogrammetry in dense urban areas

Abstract

This paper proposes a methodology to select passpoints from images obtained using close-range photogrammetry. In this method, matches on stereo-pairs are extracted using Scale-Invariant Feature transform (SIFT) (Lowe, 2004), and erroneous matches are removed using Random Sample Consensus (RANSAC) (Fischler et al, 1981). At this stage, a lot of candidates of passpoints are available, and the number of points should be reduced to save computation time for external orientation. Therefore, limited number of passpoints are selected in terms of spatial dispersion by using the score obtained by SIFT. As a result, almost all erroneous matches could be removed and the validation result demonstrated that the accuracy of segment lengths was acceptable.