Automated 3D-Objectdocumentation on the Base of an Image Set

Sebastian Vetter, Gunnar Siedler


Digital stereo-photogrammetry allows users an automatic evaluation of the spatial dimension and the surface texture of objects. The integration of image analysis techniques simplifies the automation of evaluation of large image sets and offers a high accuracy [1]. Due to the substantial similarities of stereoscopic image pairs, correlation techniques provide measurements of subpixel precision for corresponding image points. With the help of an automated point search algorithm in image sets identical points are used to associate pairs of images to stereo models and group them. The found identical points in all images are basis for calculation of the relative orientation of each stereo model as well as defining the relation of neighboured stereo models. By using proper filter strategies incorrect points are removed and the relative orientation of the stereo model can be made automatically. With the help of 3D-reference points or distances at the object or a defined distance of camera basis the stereo model is orientated absolute. An adapted expansion- and matching algorithm offers the possibility to scan the object surface automatically. The result is a three dimensional point cloud; the scan resolution depends on image quality. With the integration of the iterative closest point- algorithm (ICP) these partial point clouds are fitted to a total point cloud. In this way, 3D-reference points are not necessary. With the help of the implemented triangulation algorithm a digital surface models (DSM) can be created. The texturing can be made automatically by the usage of the images that were used for scanning the object surface. It is possible to texture the surface model directly or to generate orthophotos automatically. By using of calibrated digital SLR cameras with full frame sensor a high accuracy can be reached. A big advantage is the possibility to control the accuracy and quality of the 3d-objectdocumentation with the resolution of the images. The procedure described here is implemented in software Metigo 3D.


3d-objectdocumentation, textured surface model, orthophotos, image matching, point cloud


Henze, F.; Siedler, G.; Vetter, S.: Integration automatisierter Verfahren der digitalen Bildverarbeitung in einem Stereoauswertesystem, 26. Wissenschaftlich-Technische Jahrestagung der DGPF, Berlin, 11.– 13.09.2006, Band 15, S. 239 - 246

Vetter, S.: Generierung digitaler Oberflächenmodelle (DOM) im Bereich der Architekturphotogrammetrie, diploma thesis (unpublished), HTWK Leipzig, Germany, 2005

Heinrich, M.: Markante Punkte und 3D- Objektkanten in einem Oberflächenmodel, diploma thesis (unpublished), HTWK Leipzig, Germany, 2010

Bernardini, F., Mittleman, J., Rushmeier, H., Silva, C., Taubin, G.: The Ball-Pivoting Algorithm for Surface Reconstruction. IEEE Transaction on Visualization and Computer Graphics, 5(4), Oct-Dec, 1999, pp. 349-359.


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