The generation of 3D information from images is a key technology in many different areas, e.g. in 3D modeling and
representation of architectural or heritage objects, in human body motion tracking and scanning, in 3D scene analysis of
traffic scenes, in industrial applications and many more. The basic concepts rely on mathematical representations of
central perspective viewing as they are widely known from photogrammetry or computer vision approaches. The
objectives of these methods differ, more or less, from high precision and well-structured measurements in (industrial)
photogrammetry to fully-automated non-structured applications in computer vision.
Accuracy and precision is a critical issue for the 3D measurement of industrial, engineering or medical objects. As state
of the art, photogrammetric multi-view measurements achieve relative precisions in the order of 1:100000 to 1:200000,
and relative accuracies with respect to retraceable lengths in the order of 1:50000 to 1:100000 of the largest object
diameter. In order to obtain these figures a number of influencing parameters have to be optimized. These are, besides
others: physical representation of object surface (targets, texture), illumination and light sources, imaging sensors,
cameras and lenses, calibration strategies (camera model), orientation strategies (bundle adjustment), image processing
of homologue features (target measurement, stereo and multi-image matching), representation of object or workpiece
coordinate systems and object scale.
The paper discusses the above mentioned parameters and offers strategies for obtaining highest accuracy in object space.
Practical examples of high-quality stereo camera measurements and multi-image applications are used to prove the
relevance of high accuracy in different applications, ranging from medical navigation to static and dynamic industrial
measurements. In addition, standards for accuracy verifications are presented and demonstrated by practical examples