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Yayın Co-registration of surfaces by 3D least squares matching(Amer Soc Photogrammetry, 2010-03) Akça, Mehmet DevrimA 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.Yayın Photogrammetric deformation monitoring of the second Bosphorus Bridge in Istanbul(International Society for Photogrammetry and Remote Sensing, 2014) Avşar, Özgür; Akça, Mehmet Devrim; Altan, Mehmet OrhanImproving 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.Yayın Co-registration of 3d point clouds by using an errors-in-variables model(Copernicus Gesellschaft MBH, 2012-08-25) Aydar, Umut; Altan, Mehmet Orhan; Akyılmaz, Orhan; Akça, Mehmet DevrimCo-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.Yayın Determining pull - out deformations of bonded metal anchors embedded in concrete by means of photogrammetry(International Society for Photogrammetry and Remote Sensing, 2012) Avşar, Edip Özgür; Altan, Mehmet Orhan; Doğan, Umut Anıl; Akça, Mehmet DevrimChemical 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.Yayın Quality assessment of 3D building data(Wiley-Blackwell Publishing, 2010-12) Akça, Mehmet Devrim; Freeman, Mark; Sargent, Isabel; Gruen, Armin W.Three-dimensional building models are often now produced from lidar and photogrammetric data. The quality control of these models is a relevant issue both from the scientific and practical points of view. This work presents a method for the quality control of such models. The input model (3D building data) is co-registered to the verification data using a 3D surface matching method. The 3D surface matching evaluates the Euclidean distances between the verification and input data-sets. The Euclidean distances give appropriate metrics for the 3D model quality. This metric is independent of the method of data capture. The proposed method can favourably address the reference system accuracy, positional accuracy and completeness. Three practical examples of the method are provided for demonstration.Yayın Photogrammetric monitoring of an artificially generated landslide(Copernicus GmbH, 2011-05-08) Akça, Mehmet Devrim; Gruen, Armin W.; Askarinejad, Amin; Springman, Sarah MarcellaAccording to pre-planned schedules, a series of two artificial rainfall events were applied to a forested slope in Ruedlingen, northern Switzerland. The experiments were conducted in autumn 2008 and spring 2009, the second of which resulted in mobilising about 130 m3 of debris. Both experiments were monitored by a photogrammetric camera network in order to quantify spatial and temporal changes. A 4-camera arrangement was used for the image acquisition. The cameras operated at a data acquisition rate of circa 8 frames per second (fps). Image measurements were made using the Least Squares image matching method, which was implemented in an in-house developed software package (BAAP) to compute 3D coordinates of the target points. The surface deformation was quantified by tracking the small (ping-pong and tennis) balls pegged into the ground. The average 3D point-positioning precision of ±1.6 cm was achieved in the first experiment and ±1.8 cm in the second experiment.
