Ultrahigh-speed imaging for high-impact concrete deformation analysis in pre- and post-cracking stages.

The evaluation of high-speed camera image sequence analysis results in concrete material testing under high-impact loading necessitates the consideration of the effect of the image quality on the measurement accuracy and thus on the potential of the geometric measurements derived from the image sequences. In this contribution, we evaluate the application potential of three ultrahigh-speed cameras with frame rates up to 10 Mfps to analyze the deformation of concrete specimens before and after main crack formation in bending and compression tests. Specifically, we evaluate the Kirana 7M and Shimadzu HPV-X2 cameras with ISIS sensor architecture, and the Phantom TMX 7510 camera with BSI CMOS sensor technology. Three-point bending tests and split-Hopkinson pressure bar tests are performed on 160×40×40m m 3 cuboids and on 80 mm long, 50 mm diameter cylinders. Prior to main crack formation, the displacement vector field represents the specimen deformation, with higher values indicating the position where main cracks will initiate and propagate. Deformations of 80 µm in 54 µs for a bending test and of 154 µm in 36.67 µs for a compression test could be measured. The main cracks are then detected using displacement vector field discontinuity analysis techniques, and their evolution is followed to estimate the crack propagation velocity. Average velocities in bending tests between 603 and 854 m/s have been determined over a time interval up to 40 µs. An investigation of the camera sensor operation of the three optical devices is presented to assess their suitability for deformation analysis. Laboratory tests and real experimental results show that the quality of the propagation vector field, the crack detection, and the crack tip tracking are obviously affected by the image quality, but more significantly by the spatial and temporal resolution due to the small relative step deformations.

Camera-Aided Orientation of Mobile Lidar Point Clouds Acquired from an Uncrewed Water Vehicle.

This article presents a system for recording 3D point clouds of riverbanks with a mobile lidar mounted on an uncrewed water vehicle. The focus is on the orientation of the platform and the lidar sensor. Rivers are areas where the conditions for highly accurate GNSS can be sub-optimal due to multipath effects from the water and shadowing effects by bridges, steep valleys, trees, or other objects at the riverbanks. Furthermore, a small measurement platform may have an effect on the accuracy of orientations measured by an IMU; for instance, caused by electromagnetic fields emitted by the boat rotors, the lidar, and other hardware decreasing IMU accuracy. As an alternative, we use exterior orientation parameters obtained by photogrammetric methods from the images of a camera on the boat capturing the riverbanks in time-lapse mode. Using control points and tie points on the riverbanks enables georeferenced position and orientation determination from the image data, which can then be used to transform the lidar data into a global coordinate system. The main influences on the accuracy of the camera orientations are the distance to the riverbanks, the size of the banks, and the amount of vegetation on them. Moreover, the quality of the camera orientation-based lidar point cloud also depends on the time synchronization of camera and lidar. The paper describes the data processing steps for the geometric lidar-camera integration and delivers a validation of the accuracy potential. For quality assessment of a point cloud acquired with the described method, a comparison with terrestrial laser scanning has been carried out.

Analysis of the Accuracy Potential of a Stereo High-Speed Camera System in 3D Measurements in Highly Dynamic Experiments.

In the context of setting up a stereo high-speed camera system for accurate 3D measurements in highly dynamic experiments, the potential of a "Fastcam SA-X2" stereo system is evaluated by testing different camera configurations and motion scenarios. A thorough accuracy analysis is performed using spatial rigid-body transformations and relative measurement analyses of photogrammetrically reconstructed surfaces of nondeformable objects. The effects of camera calibration, exposure time, object velocity, and object surface pattern quality on the quality of adjusted 3D coordinates are taken into consideration. While the exposure time does not significantly influence the quality of the static measurements, the results of dynamic experiments demonstrate that not only an insufficient frame rate but also an increased noise level resulting from short exposure times affects 3D coordinate accuracy. Using appropriate configurations to capture dynamic events, the errors in dynamic experiments do not differ significantly from the errors obtained in static measurements. A spatial mapping error of less than 1 µm is obtained through the experiments, with proper testing configurations for an object surface area of 5×20 mm. These findings are relevant for users of high-speed stereo imaging techniques to perform geometric 3D measurements, deformation, and crack analyses.

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives.

Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling, acquiring, sharing, managing, exploring, analyzing, synthesizing, visualizing, and evaluating data on spatio-temporal phenomena related to the Earth. As an interdisciplinary scientific discipline, it focuses on developing and adapting information technologies to understand processes on the Earth and human-place interactions, to detect and predict trends and patterns in the observed data, and to support decision making. The authors - members of DGK, the Geoinformatics division, as part of the Committee on Geodesy of the Bavarian Academy of Sciences and Humanities, representing geodetic research and university teaching in Germany - have prepared this paper as a means to point out future research questions and directions in geospatial information science. For the different facets of geospatial information science, the state of art is presented and underlined with mostly own case studies. The paper thus illustrates which contributions the German GI community makes and which research perspectives arise in geospatial information science. The paper further demonstrates that GI science, with its expertise in data acquisition and interpretation, information modeling and management, integration, decision support, visualization, and dissemination, can help solve many of the grand challenges facing society today and in the future.

Computational Optimization of the 3D Least-Squares Matching Algorithm by Direct Calculation of Normal Equations.

3D least-squares matching is an algorithm that allows to measure subvoxel-precise displacements between two data sets of computed tomography voxel data. The determination of precise displacement vector fields is an important tool for deformation analyses in in-situ X-ray micro-tomography time series. The goal of the work presented in this publication is the development and validation of an optimized algorithm for 3D least-squares matching saving computation time and memory. 3D least-squares matching is a gradient-based method to determine geometric (and optionally also radiometric) transformation parameters between consecutive cuboids in voxel data. These parameters are obtained by an iterative Gauss-Markov process. Herein, the most crucial point concerning computation time is the calculation of the normal equations using matrix multiplications. In the paper at hand, a direct normal equation computation approach is proposed, minimizing the number of computation steps. A theoretical comparison shows, that the number of multiplications is reduced by 28% and the number of additions by 17%. In a practical test, the computation time of the 3D least-squares matching algorithm was proven to be reduced by 27%.

Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests.

BACKGROUND AND AIMS: In addition to terrestrial laser scanning (TLS), mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3-D data for various applications in forest research. Using mobile platforms, the 3-D recording of large forest areas is carried out within a short space of time. Vegetation structure is described by millions of 3-D points which show an accuracy in the millimetre range and offer a powerful basis for automated vegetation modelling. The successful extraction of single trees from the point cloud is essential for further evaluations and modelling at the individual-tree level, such as volume determination, quantitative structure modelling or local neighbourhood analyses. However, high-precision automated tree segmentation is challenging, and has so far mostly been performed using elaborate interactive segmentation methods. METHODS: Here, we present a novel segmentation algorithm to automatically segment trees in MLS point clouds, applying distance adaptivity as a function of trajectory. In addition, tree parameters are determined simultaneously. In our validation study, we used a total of 825 trees from ten sample plots to compare the data of trees segmented from MLS data with manual inventory parameters and parameters derived from semi-automatic TLS segmentation. KEY RESULTS: The tree detection rate reached 96 % on average for trees with distances up to 45 m from the trajectory. Trees were almost completely segmented up to a distance of about 30 m from the MLS trajectory. The accuracy of tree parameters was similar for MLS-segmented and TLS-segmented trees. CONCLUSIONS: Besides plot characteristics, the detection rate of trees in MLS data strongly depends on the distance to the travelled track. The algorithm presented here facilitates the acquisition of important tree parameters from MLS data, as an area-wide automated derivation can be accomplished in a very short time.

Tensile Behavior of High-Strength, Strain-Hardening Cement-Based Composites (HS-SHCC) Reinforced with Continuous Textile Made of Ultra-High-Molecular-Weight Polyethylene.

The paper at hand presents an investigation of the tensile behavior of high-strength, strain-hardening cement-based composites (HS-SHCC), reinforced with a single layer of continuous, two-dimensional textile made of ultra-high molecular weight polyethylene (UHMWPE). Uniaxial tension tests were performed on the bare UHMWPE textiles, on plain HS-SHCC, and on the hybrid fiber-reinforced composites. The bond properties between the textile yarns and the surrounding composite were investigated in single-yarn pullout experiments. In order to assess the influence of bond strength between the yarn and HS-SHCC on the tensile behavior of the composites with hybrid fiber reinforcement, the textile samples were analyzed both with, and without, an additional coating of epoxy resin and sand. Compared to the composites reinforced with carbon yarns in previous studies by the authors, the high elongation capacity of the UHMWPE textile established the higher strain capacity of the hybrid fiber-reinforced composites, and showed superior energy absorption capacity up to failure. The UHMWPE textile limited the average crack width in comparison with that of plain HS-SHCC, but led to slightly larger crack widths when compared to equivalent composites reinforced with carbon textile, the reason for which was traced back to the lower Young's modulus and the higher elongation capacity of the polymer textile.

Crack Propagation Velocity Determination by High-speed Camera Image Sequence Processing.

The determination of crack propagation velocities can provide valuable information for a better understanding of damage processes of concrete. The spatio-temporal analysis of crack patterns developing at a speed of several hundred meters per second is a rather challenging task. In the paper, a photogrammetric procedure for the determination of crack propagation velocities in concrete specimens using high-speed camera image sequences is presented. A cascaded image sequence processing which starts with the computation of displacement vector fields for a dense pattern of points on the specimen's surface between consecutive time steps of the image sequence chain has been developed. These surface points are triangulated into a mesh, and as representations of cracks, discontinuities in the displacement vector fields are found by a deformation analysis applied to all triangles of the mesh. Connected components of the deformed triangles are computed using region-growing techniques. Then, the crack tips are determined using the principal component analysis. The tips are tracked in the image sequence and the velocities between the time stamps of the images are derived. A major advantage of this method as compared to the established techniques is in the fact that it allows spatio-temporally resolved, full-field measurements rather than point-wise measurements. Furthermore, information on the crack width can be obtained simultaneously. To validate the experimentation, the authors processed image sequences of tests on four compact-tension specimens performed on a split-Hopkinson tension bar. The images were taken by a high-speed camera at a frame rate of 160,000 images per second. By applying the developed image sequence processing procedure to these datasets, crack propagation velocities of about 800 m/s were determined with a precision in the order of 50 m/s.

Assessing the Influence of Temperature Changes on the Geometric Stability of Smartphone- and Raspberry Pi Cameras.

Knowledge about the interior and exterior camera orientation parameters is required to establish the relationship between 2D image content and 3D object data. Camera calibration is used to determine the interior orientation parameters, which are valid as long as the camera remains stable. However, information about the temporal stability of low-cost cameras due to the physical impact of temperature changes, such as those in smartphones, is still missing. This study investigates on the one hand the influence of heat dissipating smartphone components at the geometric integrity of implemented cameras and on the other hand the impact of ambient temperature changes at the geometry of uncoupled low-cost cameras considering a Raspberry Pi camera module that is exposed to controlled thermal radiation changes. If these impacts are neglected, transferring image measurements into object space will lead to wrong measurements due to high correlations between temperature and camera's geometric stability. Monte-Carlo simulation is used to simulate temperature-related variations of the interior orientation parameters to assess the extent of potential errors in the 3D data ranging from a few millimetres up to five centimetres on a target in X- and Y- direction. The target is positioned at a distance of 10 m to the camera and the Z-axis is aligned with camera's depth direction.

Non-invasive estimation of brain-volume in infants.

BACKGROUND: Neurological development is determined by brain growth. Methods to measure total brain volume (TBV) in clinical settings are limited. MR-imaging represents the gold-standard. AIMS: The present study tests the hypotheses that in infants without any brain pathology, TBV - as determined by MRI - can be accurately estimated by cranial volume (CrV), measured by 3D-laser scanning. In case of good correlation of CrV with TBV it was further tested, whether CrV can be also estimated by (I) head circumference (HC) or (II) by other technology than laser scanning. STUDY DESIGN & SUBJECTS: To test the hypothesis, that TBV can be reliably estimated by CrV-measurement, data from routine MRI and 3D-laser-scanner measurements were analyzed in infants if no major structural brain anomaly was found in MR-imaging. To test whether CrV can be predicted by HC-measurements during infancy, data from routine follow-up visits were used from preterms born in a two year period. Preterms are invited for a routine follow-up visit (which includes laser scanning of the head) at an age of 3 months and, for further follow-ups at 6, 9 or 12 months. To compare accuracy of CrV measurement by other techniques, a puppet head was measured, using different 3D-measurement principles: (i) Structured light projection system, (ii) The non-invasive laser-shape-digitizer, and (iii) Structure-from-motion (SFM) technique. OUTCOME MEASURES: TBV was compared with CrV using a Passing-Bablok-Regression. To determine how well HC predicts CrV, the coefficient of determinant (R2) was calculated for each age group. RESULTS: CrV and TBV of 25 infants (median age 19 month, body weight of 11 kg) showed a median bias of -86.7 mm3 with a slightly smaller TBV (median of 1034.1 mm3, IQR 875.9 … 1179.8 mm3) than CrV (median 1092.2, IQR 950.5 … 1258.4 mm3). CrV was poorly estimated by HC, with R2 between 0.79 and 0.87 at 3 and 9 month of age respectively. For the non-invasive laser-shape-digitizer and the SFM-technique the accuracy was good (radial coordinate differences ±0.3 vs. ±0.5 mm). CONCLUSION: The present study provides convincing evidence that CrV can be used to estimate TBV in routine care, whereas HC is a poor predictor of individual CrV.

On the Accuracy Potential in Underwater/Multimedia Photogrammetry.

Underwater applications of photogrammetric measurement techniques usually need to deal with multimedia photogrammetry aspects, which are characterized by the necessity of handling optical rays that are refracted at interfaces between optical media with different refractive indices according to Snell's Law. This so-called multimedia geometry has to be incorporated into geometric models in order to achieve correct measurement results. The paper shows a flexible yet strict geometric model for the handling of refraction effects on the optical path, which can be implemented as a module into photogrammetric standard tools such as spatial resection, spatial intersection, bundle adjustment or epipolar line computation. The module is especially well suited for applications, where an object in water is observed by cameras in air through one or more planar glass interfaces, as it allows for some simplifications here. In the second part of the paper, several aspects, which are relevant for an assessment of the accuracy potential in underwater/multimedia photogrammetry, are discussed. These aspects include network geometry and interface planarity issues as well as effects caused by refractive index variations and dispersion and diffusion under water. All these factors contribute to a rather significant degradation of the geometric accuracy potential in underwater/multimedia photogrammetry. In practical experiments, a degradation of the quality of results by a factor two could be determined under relatively favorable conditions.