Photogrammetric monitoring of an artificially generated shallow landslide

An artificial rainfall event was applied to a forested slope in Ruedlingen, northern Switzerland. The experiment triggered a landslide which resulted in mobilising about 130m3 of debris. The event was monitored by a photogrammetric network of four cameras, operating at 5 to 8 frames per second, in order to quantify spatial and temporal changes by tracking tennis balls pegged into the ground. Image measurements were performed using automated image matching methods, implemented through a software package developed in-house. Three-dimensional coordinates of the target points were estimated by running a customised type of bundle adjustment, achieving a positioning precision of +/- 1 center dot 8cm.This research was funded by the Competence Centre for Environment and Sustainability (CCES) within the framework of the TRAMM project. Amin Askarinejad, Professor Dr Sarah M. Springman, Marco Sperl, Stefan Moser, Ernst Bleiker, Felix Wietlisbach and Peter Kienzler kindly contributed to the work. The author is grateful to the Gemeinde of Ruedlingen and their President, Mrs Katy Leutenegger, for giving permission to carry out this experiment on their land. The author gratefully thanks Professor Dr Armin Gruen for his help and valuable comments. The author also thanks the anonymous reviewers for their valuable criticism and suggestions that improved the quality of the paperPublisher's VersionAuthor Post Prin

Co-registration of surfaces by 3D least squares matching

A method for the automatic co-registration of 3D surfaces is presented. Die method utilizes the mathematical model of Least Squares 2D image matching and extends it for solving the 3D surface matching problem The transformation parameters of the search surfaces are estimated with respect to a template surface. The solution is achieved when the sum of the squares of the 3D Spatial (Euclidean) distances between the surfaces are minimized. The parameter estimation is achieved using the Generalized Gauss-Markov model. Execution level implementation details are given. Apart from the co-registration of the point clouds generated from spacaborne airborne and terrestinal sensors and techniques. the proposed method is also useful for change detection, 3D comparison, and quality assessment tasks Experiments, terrain data examples show file capabilities of the method.Publisher's Versio

3D modeling of cultural heritage objects with a structured light system

3D modeling of cultural heritage objects is an expanding application area. The selection of the right technology is very important and strictly related to the project requirements, budget and user's experience. The triangulation based active sensors, e.g. structured light systems are used for many kids of 3D object reconstruction tasks and in particular for 3D recording of cultural heritage objects. This study presents the experiences in the results of two such projects in which a close-range structured light system is used for the 3D digitization. The paper includes the essential steps of the 3D object modeling pipeline, i.e. digitization, registration, surface triangulation, editing, texture mapping and visualization. The capabilities of the used hardware and software are addressed. Particular emphasis is given to a coded structured light system as an option for data acquisition.Publisher's Versio

Laboratory flume experiment with a coded structured light system

The topography of inland deltas is influenced chiefly by the water-sediment balance in distributary channels and local evaporation and seepage rates. In a previous study, a reduced complexity model has been applied to simulate the process of inland delta formation. Results have been compared with the Okavango Delta, Botswana and with a laboratory experiment. Both in the macro scale and the micro scale cases, high quality digital elevation models (DEM) are essential. This work elaborates the laboratory experiment where an artificial inland delta is generated on laboratory scale and its topography is measured using a Breuckmann 3D scanner. The space-time evolution of the inland delta is monitored in the consecutive DEM layers. Regarding the 1.0m x 1.0m x 0.3m size of the working area, better than 100 micron precision is achieved which gives a relative precision of 1/10 000. The entire 3D modelling workflow is presented in terms of scanning, co-registration, surface generation, editing, and visualization steps. The co-registered high resolution topographic data allows us to analyse the stratigraphy patterns of the experiment and gain quantitative insight into the spatio-temporal evolution of the delta formation process.Publisher's Versio

Photogrammetric deformation monitoring of the second Bosphorus Bridge in Istanbul

Improving the efficiency of bridge inspection and minimizing the impact of dynamic load on the long term deterioration of the bridge structure reduces maintenance and upkeep costs whilst also improving bridge longevity and safety. This paper presents the results of an on-going project whose ultimate goal is the real-time photogrammetric monitoring the structural deformations of the second Bosphorus Bridge of Istanbul.Publisher's Versio

An emprical point error model for TLS derived point clouds

The random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds. A priori precisions of basic TLS observations, which are the range, horizontal angle and vertical angle, are determined by predefined and practical measurement configurations, performed at real-world test environments. A priori precision of horizontal (σθ) and vertical (σα) angles are constant for each point of a data set, and can directly be determined through the repetitive scanning of the same environment. In our practical tests, precisions of the horizontal and vertical angles were found as σθ=±36.6 and σα=±17.8, respectively. On the other hand, a priori precision of the range observation (σρ) is assumed to be a function of range, incidence angle of the incoming laser ray, and reflectivity of object surface. Hence, it is a variable, and computed for each point individually by employing an empirically developed formula varying as σρ=±2a'12 mm for a FARO Focus X330 laser scanner. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. The usability and feasibility of the model was investigated in real world scenarios. These investigations validated the suitability and practicality of the proposed method.This research was funded by TUBITAK - The Scientific and Technological Research Council of Turkey (Project ID: 115Y239) and by the Scientific Research Projects of Bulent Ecevit University (Project ID: 2015-47912266-01)Publisher's Versio

Stochastic surface mesh reconstruction

This research was funded by TUBITAK – The Scientific and Technological Research Council of Turkey (Project ID: 115Y239) and by the Scientific Research Projects of Bülent Ecevit University (Project ID: 2015-47912266-01)A generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with developing an anisotropic point error model, which is capable of computing the theoretical precisions of 3D coordinates of each individual point in the point cloud. The magnitude and direction of the errors are represented in the form of error ellipsoids. The following second step is focused on the stochastic surface mesh reconstruction. It exploits the previously determined error ellipsoids by computing a point-wise quality measure, which takes into account the semi-diagonal axis length of the error ellipsoid. The points only with the least errors are used in the surface triangulation. The remaining ones are automatically discarded.Publisher's Versio

Total least squares registration of 3D surfaces

Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of coregistration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In computer vision and photogrammetry domain one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D Least Squares (LS) matching methods as well (Gruen and Akca, 2005). The co-registration methods commonly use the least squares (LS) estimation method in which the unknown transformation parameters of the (floating) search surface is functionally related to the observation of the (fixed) template surface. Here, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values of the search surface. . This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a method where the stochastic properties of both the observations and the parameters are considered under an errors-in-variables (EIV) model. The experiments have been carried out using diverse laser scanning data sets and the results of EIV with the ICP and the conventional LS matching methods have been compared.Publisher's Versio

Co-registration of 3d point clouds by using an errors-in-variables model

Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D least squares (LS) matching methods as well. In most of the co-registration methods, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values. This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a new method where the stochastic properties of both (template and search) surfaces are considered under an errors-in-variables (EIV) model. The experiments have been carried out using a close range laser scanning data set and the results of the conventional and EIV types of the ICP matching methods have been compared.Publisher's Versio

Determining pull - out deformations of bonded metal anchors embedded in concrete by means of photogrammetry

Chemical anchorages are applied in many engineering implementations, particularly strengthening of reinforced concrete structures. During strengthening procedure; chemical anchorages should be tested, since they supply to transfer the load between existing construction elements and newly added elements. Therefore; the study of the quality of chemical anchorages is an important issue in construction materials science. In this context; the most important experiment is to determine the pull-out loads of embedded anchorage reinforcement by applying axial loads. In this study; it is aimed to determine the displacements of steel reinforcements, embedded into concrete by using chemical anchorages, while applying axial pulling loads. In order to determine the displacements and load - deformation graphs; starting conditions and every 10 bar pressure applied conditions of the steel reinforcements were captured by the cameras. The obtained images were evaluated by using photogrammetric software. Based on the photogrammetric post-processing results, the load - deformation graphs were plotted and the loads at loss of adhesion were determined.Publisher's Versio