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G. Karras

Bio: G. Karras is an academic researcher from National Technical University of Athens. The author has contributed to research in topics: Photogrammetry & Bundle adjustment. The author has an hindex of 13, co-authored 42 publications receiving 471 citations. Previous affiliations of G. Karras include Technological Educational Institute of Athens & National Technical University.

Papers
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Journal ArticleDOI
TL;DR: In this article, an approach for the automatic estimation of interior orientation from images with three vanishing points of orthogonal directions is presented. But this approach is limited to single images and cannot handle images with multiple vanishing points.
Abstract: Camera calibration is a fundamental task in photogrammetry and computer vision. This paper presents an approach for the automatic estimation of interior orientation from images with three vanishing points of orthogonal directions. Extraction of image line segments and their clustering into groups corresponding to three dominant vanishing points are performed without any human interaction. Camera parameters (camera constant, location of principal point, and two coefficients of radial lens distortion) and the vanishing points are estimated in a one-step adjustment of all participating image points. The approach may function in a single image mode, but is also capable of handling input from independent images (i.e. images not necessarily of the same object) with three and/or two vanishing points in a common solution. The reported experimental tests indicate that, within certain limits, results from single images compare satisfactorily with those from multi-image bundle adjustment.

65 citations

Journal ArticleDOI
TL;DR: It is shown that an adaptive local stereo-method of high computational efficiency may provide accurate 3D reconstructions under various scenarios, or even outperform global optimizations, and it is demonstrated that census matching cost on image gradients is more robust, and the absolute difference in colour and in principal image derivatives is exponentially combined.
Abstract: Defining pixel correspondences among images is a fundamental process in fully automating image-based 3D reconstruction. In this contribution, we show that an adaptive local stereo-method of high computational efficiency may provide accurate 3D reconstructions under various scenarios, or even outperform global optimizations. We demonstrate that census matching cost on image gradients is more robust, and we exponentially combine it with the absolute difference in colour and in principal image derivatives. An aggregated cost volume is computed by linearly expanded cross skeleton support regions. A novel consideration is the smoothing of the cost volume via a modified 3D Gaussian kernel, which is geometrically constrained; this offers 3D support to cost computation in order to relax the inherent assumption of “fronto-parallelism” in local methods. The above steps are integrated into a hierarchical scheme, which exploits adaptive windows. Hence, failures around surface discontinuities, typical in hierarchical matching, are addressed. Extensive results are presented for datasets from popular benchmarks as well as for aerial and high-resolution close-range images.

62 citations

Journal Article
TL;DR: In this article, a method for matching pairs of digital elevation models (DEMs), based on surface shape and without control points, has been evaluated in close-range photogrammetry, showing that the influence of orientation errors has been effectively removed from the transformed models.
Abstract: A method for matching pairs of digital elevation models (DEMs), based on surface shape and without control points, has been evaluated in close-range photogrammetry. Results presented for 30 DEM pairs of the human body trunk and of varying relief indicate that the influence of orientation errors has been effectively removed from the transformed models. The final RMS differences in relief are close to the RMS errors of the elevations themselves. Introduction of gross error detection techniques, such as «data-snooping,» simultaneously allows orientation based on similar model regions and localization of deformations. The magnitude of the latter is adequately estimated using the weight cofactor matrix of residuals

45 citations

Journal ArticleDOI
TL;DR: In this article, the authors synthesize related work in photogrammetry and computer graphics/vision to automatically produce orthographic and perspective views based on fully 3D surface data (supplied by laser scanning).
Abstract: Conventional orthorectification software cannot handle surface occlusions and image visibility. The approach presented here synthesizes related work in photogrammetry and computer graphics/vision to automatically produce orthographic and perspective views based on fully 3D surface data (supplied by laser scanning). Surface occlusions in the direction of projection are detected to create the depth map of the new image. This information allows identifying, by visibility checking through back-projection of surface triangles, all source images which are entitled to contribute color to each pixel of the novel image. Weighted texture blending allows regulating the local radiometric contribution of each source image involved, while outlying color values are automatically discarded with a basic statistical test. Experimental results from a close-range project indicate that this fusion of laser scanning with multiview photogrammetry could indeed combine geometric accuracy with high visual quality and speed. A discussion of intended improvements of the algorithm is also included.

25 citations

01 Jan 1999
TL;DR: In this paper, the Intergraph ImageStation SSK system was used in the photogrammetric documentation of an archaeological site in Athens with abrupt changes in relief, taken from a small balloon with a 35 mm amateur camera and wide-angle lens.
Abstract: Combined with elevation data, orthomosaics are now among the main (end or intermediate) photogrammetric products for archaeological documentation. But DEM collection/editing and orthorectification/orthomosaicking may well necessitate powerful tools − according to object size, scale, accuracy requirements and, hence, number of images and scanning resolution. Here, digital photogrammetric workstations in their new, relatively low-cost, versions are obvious choices. On the other hand, imagery may be non-metric taken from ‘unstable’ platforms. This paper discusses our experiences with the Intergraph ImageStation SSK system in the photogrammetric documentation of an archaeological site in Athens with abrupt changes in relief. Taken from a small balloon with a 35 mm amateur camera and wide-angle lens, the 12 images formed a strip of unconventional geometry (large variations in scale and rotations), for which extensive geodetic control was available for checking purposes. Correcting radial symmetric lens distortion proved to be of paramount importance for reliable elevations and paralax-free models. It was concluded that, given certain conditions, digital photogrammetric workstations may indeed be efficient in handling demanding image configurations from non-metric sources.

22 citations


Cited by
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Journal ArticleDOI
TL;DR: This surface matching technique is a generalization of the least squares image matching concept and offers high flexibility for any kind of 3D surface correspondence problem, as well as statistical tools for the analysis of the quality of final matching results.
Abstract: The automatic co-registration of point clouds, representing 3D surfaces, is a relevant problem in 3D modeling. This multiple registration problem can be defined as a surface matching task. We treat it as least squares matching of overlapping surfaces. The surface may have been digitized/sampled point by point using a laser scanner device, a photogrammetric method or other surface measurement techniques. Our proposed method estimates the transformation parameters of one or more 3D search surfaces with respect to a 3D template surface, using the Generalized Gauss–Markoff model, minimizing the sum of squares of the Euclidean distances between the surfaces. This formulation gives the opportunity of matching arbitrarily oriented 3D surface patches. It fully considers 3D geometry. Besides the mathematical model and execution aspects we address the further extensions of the basic model. We also show how this method can be used for curve matching in 3D space and matching of curves to surfaces. Some practical examples based on the registration of close-range laser scanner and photogrammetric point clouds are presented for the demonstration of the method. This surface matching technique is a generalization of the least squares image matching concept and offers high flexibility for any kind of 3D surface correspondence problem, as well as statistical tools for the analysis of the quality of final matching results.

569 citations

Book ChapterDOI
06 Sep 2014
TL;DR: This work presents the first comprehensive texturing framework for large-scale, real-world 3D reconstructions, and addresses most challenges occurring in such reconstructions: the large number of input images, their drastically varying properties such as image scale, (out-of-focus) blur, exposure variation, and occluders.
Abstract: 3D reconstruction pipelines using structure-from-motion and multi-view stereo techniques are today able to reconstruct impressive, large-scale geometry models from images but do not yield textured results. Current texture creation methods are unable to handle the complexity and scale of these models. We therefore present the first comprehensive texturing framework for large-scale, real-world 3D reconstructions. Our method addresses most challenges occurring in such reconstructions: the large number of input images, their drastically varying properties such as image scale, (out-of-focus) blur, exposure variation, and occluders (e.g., moving plants or pedestrians). Using the proposed technique, we are able to texture datasets that are several orders of magnitude larger and far more challenging than shown in related work.

296 citations

Journal ArticleDOI
TL;DR: In this article, a high-resolution remote sensing system for aerial surveys by blimp or kite has been developed which meets spatial and temporal image resolutions required for short-term gully monitoring.

220 citations

Journal ArticleDOI
TL;DR: This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest.
Abstract: Due to the unprecedented technology development of sensors, platforms and algorithms for 3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the form of image based, Light Detection and Ranging (LiDAR) based point clouds, Digital Elevation Models (DEM) and 3D city models, become more accessible than ever before Change detection (CD) or time-series data analysis in 3D has gained great attention due to its capability of providing volumetric dynamics to facilitate more applications and provide more accurate results The state-of-the-art CD reviews aim to provide a comprehensive synthesis and to simplify the taxonomy of the traditional remote sensing CD techniques, which mainly sit within the boundary of 2D image/spectrum analysis, largely ignoring the particularities of 3D aspects of the data The inclusion of 3D data for change detection (termed 3D CD), not only provides a source with different modality for analysis, but also transcends the border of traditional top-view 2D pixel/object-based analysis to highly detailed, oblique view or voxel-based geometric analysis This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest We first describe the general considerations of 3D CD problems in different processing stages and identify CD types based on the information used, being the geometric comparison and geometric-spectral analysis We then summarize relevant works and practices in urban, environment, ecology and civil applications, etc Given the broad spectrum of applications and different types of 3D data, we discuss important issues in 3D CD methods Finally, we present concluding remarks in algorithmic aspects of 3D CD

200 citations