Orientation and 3D modeling from markerless terrestrial images: combining accuracy with automation

In this paper an automated methodology is presented (i) to orient a set of close-range images captured with a calibrated camera, and (ii) to extract dense and accurate point clouds starting from the estimated orientation parameters. The whole procedure combines different algorithms and techniques in order to obtain accurate 3D reconstructions in an automatic way. The exterior orientation parameters are estimated using a photogrammetric bundle adjustment with the image correspondences detected using area- and feature-based matching algorithms. Surface measurements are then performed using advanced multi-image matching techniques based on multiple image primitives. To demonstrate the reliability, precision and robustness of the procedure, several tests on different kinds of free-form objects are illustrated and discussed in the paper. Three-dimensional comparisons with range-based data are also carried out.