ABSTRACT:Stereo endoscopes for minimally invasive surgery have been available on the market for several years and are well established in some areas. In practice, they offer a stereoscopic view to the surgeon but are not yet intended for 3D measurements. However, using current knowledge about the camera system and the difficult conditions in object space, it is possible to reconstruct a highly accurate surface model of the current endoscopic view. In particular for medical interventions, a highly reliable point cloud and real-time computation are required. To obtain good reliability, a miniaturised trinocular camera system is introduced that reduces the amount of outliers. To reduce computation time, an approach for generation of rectified image triplets and their corresponding interior and exterior camera parameters has been developed. With these modified and parameterised images it is possible to directly process 3D measurements in object space. Accordingly, an efficient semi-global optimisation is implemented by the authors. In this paper the special camera system, the rectification approach and the applied methodology of matching in rectified image triplets are explained. Finally, first results are presented. In conclusion, the trinocular camera system provides more reliable point clouds than a binocular one, especially for areas with repetitive or poor texture. Currently, the benefit of the third camera is not as great as desired.
ABSTRACT:In this paper a method is presented which allows the measurement of deflections and torsion by means of the silhouette of an object in images. The method is based on a finite element description of a beam. The benefit of this method is the determination of the deformation out of the silhouette of an object in images without the need of signalization. The presented method is tested against simulated data as well as against real objects in laboratory tests. As an outlook the presented method can be further modified. By combination with a laser scanner it seems to be possible to replace the CAD model of an object with the point clouds of one or more kinematic laser scans.
ABSTRACT:This paper examines the influence of raw image preprocessing and other selected processes on the accuracy of close-range photogrammetric measurement. The examined processes and features includes: raw image preprocessing, sensor unflatness, distancedependent lens distortion, extending the input observations (image measurements) by incorporating all RGB colour channels, ellipse centre eccentricity and target detecting. The examination of each effect is carried out experimentally by performing the validation procedure proposed in the German VDI guideline 2634/1. The validation procedure is based on performing standard photogrammetric measurements of high-accurate calibrated measuring lines (multi-scale bars) with known lengths (typical uncertainty = 5 µm at 2 sigma). The comparison of the measured lengths with the known values gives the maximum length measurement error LME, which characterize the accuracy of the validated photogrammetric system. For higher reliability the VDI test field was photographed ten times independently with the same configuration and camera settings. The images were acquired with the metric ALPA 12WA camera. The tests are performed on all ten measurements which gives the possibility to measure the repeatability of the estimated parameters as well. The influences are examined by comparing the quality characteristics of the reference and tested settings.
ABSTRACT:This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.
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