3D Reconstruction

 

Efficient 3D Scene Abstraction Using Line Segments
Manuel Hofer, Michael Maurer, Horst Bischof. In Computer Vision and Image Understanding (CVIU), 2016.

CVIU 2016

Extracting 3D information from a moving camera is traditionally based on interest point detection and matching. This is especially challenging in urban indoor- and outdoor environments, where the number of distinctive interest points is naturally limited. While common Structure-from-Motion (SfM) approaches usually manage to obtain the correct camera poses, the number of accurate 3D points is very small due to the low number of matchable features. Subsequent Multi-view Stereo approaches may help to overcome this problem, but suffer from a high computational complexity. We propose a novel approach for the task of 3D scene abstraction, which uses straight line segments as underlying features. We use purely geometric constraints to match 2D line segments from different images, and formulate the reconstruction procedure as a graph-clustering problem. We show that our method generates accurate 3D models with low computational costs, which makes it especially useful for large-scale urban datasets.

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Line3D - Efficient 3D Scene Abstraction for the Built Environment
Manuel Hofer, Michael Maurer, Horst Bischof. In Proceedings of the 37th German Conference on Pattern Recognition (GCPR), Aachen, 2015.

GCPR 2015

Extracting 3D information from a moving camera is traditionally based on interest point detection and matching. This is especially challenging in the built environment, where the number of distinctive interest points is naturally limited. While common Structure-from-Motion (SfM) approaches usually manage to obtain the correct camera poses, the number of accurate 3D points is very small due to the low number of matchable features. Subsequent Multi-view Stereo approaches may help to overcome this problem, but suffer from a high computational complexity. We propose a novel approach for the task of 3D scene abstraction, which uses straight line segments as underlying features. We use purely geometric constraints to match 2D line segments from different images, and formulate the reconstruction procedure as a graph-clustering problem. We show that our method generates accurate 3D models, with a low computational overhead compared to SfM alone.

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Building with Drones: Accurate 3D Facade Reconstruction using MAVs
Shreyansh Daftry, Christof Hoppe, Horst Bischof. In Proceedings of International Conference on Robotics and Automation (ICRA), Seattle, 2015.

ICRA 2015

Automatic reconstruction of 3D models from images using multi-view Structure-from-Motion methods has been one of the most fruitful outcomes of computer vision. These advances combined with the growing popularity of Micro Aerial Vehicles as an autonomous imaging platform, have made 3D vision tools ubiquitous for large number of Architecture, Engineering and Construction applications among audiences, mostly unskilled in computer vision. However, to obtain high-resolution and accurate reconstructions from a large-scale object using SfM, there are many critical constraints on the quality of image data, which often become sources of inaccuracy as the current 3D reconstruction pipelines do not facilitate the users to determine the fidelity of input data during the image acquisition. In this paper, we present and advocate a closed-loop interactive approach that performs incremental reconstruction in real-time and gives users an online feedback about the quality parameters like Ground Sampling Distance (GSD), image redundancy, etc on a surface mesh. We also propose a novel multi-scale camera network design to prevent scene drift caused by incremental map building, and release the first multi-scale image sequence dataset as a benchmark. Further, we evaluate our system on real outdoor scenes, and show that our interactive pipeline combined with a multi-scale camera network approach provides compelling accuracy in multi-view reconstruction tasks when compared against the state-of-the-art methods.

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Improving Sparse 3D Models for Man-Made Environments Using Line-Based 3D Reconstruction
Manuel Hofer, Michael Maurer, Horst Bischof. In Proceedings of International Conference on 3D Vision (3DV), Tokyo, 2014.

3DV 2014

Traditional Structure-from-Motion (SfM) approaches work well for richly textured scenes with a high number of distinctive feature points. Since man-made environments often contain textureless objects, the resulting point cloud suffers from a low density in corresponding scene parts. The missing 3D information heavily affects all kinds of subsequent post-processing tasks (e.g. meshing), and significantly decreases the visual appearance of the resulting 3D model. We propose a novel 3D reconstruction approach, which uses the output of conventional SfM pipelines to generate additional complementary 3D information, by exploiting line segments. We use appearance-less epipolar guided line matching to create a potentially large set of 3D line hypotheses, which are then verified using a global graph clustering procedure. We show that our proposed method outperforms the current state-of-the-art in terms of runtime and accuracy, as well as visual appearance of the resulting reconstructions.

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Automated End-to-End Workflow for Precise and Geo-accurate Reconstructions using Fiducial Markers
Markus Rumpler, Shreyansh Daftry, Alexander Tscharf, Rudolf Prettenthaler, Christof Hoppe, Gerhard Mayer, Horst Bischof. In ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014.

PCV 2014

Photogrammetric computer vision systems have been well established in many scientific and commercial fields during the last decades. Recent developments in image-based 3D reconstruction systems in conjunction with the availability of affordable high quality digital consumer grade cameras have resulted in an easy way of creating visually appealing 3D models. However, many of these methods require manual steps in the processing chain and for many photogrammetric applications such as mapping, recurrent topographic surveys or architectural and archaeological 3D documentations, high accuracy in a geo-coordinate system is required which often cannot be guaranteed. Hence, in this paper we present and advocate a fully automated end-to-end workflow for precise and geo-accurate 3D reconstructions using fiducial markers. We integrate an automatic camera calibration and georeferencing method into our image-based reconstruction pipeline based on binary-coded fiducial markers as artificial, individually identifiable landmarks in the scene. Additionally, we facilitate the use of these markers in conjunction with known ground control points (GCP) in the bundle adjustment, and use an online feedback method that allows assessment of the final reconstruction quality in terms of image overlap, ground sampling distance (GSD) and completeness, and thus provides flexibility to adopt the image acquisition strategy already during image recording. An extensive set of experiments is presented which demonstrate the accuracy benefits to obtain a highly accurate and geographically aligned reconstruction with an absolute point position uncertainty of about 1.5 times the ground sampling distance.

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Semi-Global 3D Line Modeling for Incremental Structure-from-Motion
Manuel Hofer, Michael Donoser, Horst Bischof. In Proceedings of the British Machine Vision Conference (BMVC), Nottingham (UK), 2014.

BMVC 2014

Structure-from-Motion (SfM) approaches, which are conventionally based on local interest point matches, tend to work well for richly textured indoor- and outdoor environments. However, in less textured scene areas the density of the resulting point cloud suffers from the lower number of matchable interest points. This significantly affects subsequent computer vision tasks like image based localization, surface extraction or visual navigation. In this paper, we propose a novel 3D reconstruction approach that increases the amount of 3D information in the reconstruction by exploiting line segments as complementary features. We introduce an efficient and effective semi-global approach, which takes into account local (per 2D line segment) as well as global (graph clustering) 3D line hypotheses constellations. Our approach outperforms the state-of-the-art in terms of accuracy, with comparable runtime.

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Flexible and User-Centric Camera Calibration using Planar Fiducial Markers
Shreyansh Daftry, Michael Maurer, Andreas Wendel, Horst Bischof. In Proceedings of the British Machine Vision Conference (BMVC), Bristol (UK), 2013.

BMVC 2013

The benefit of accurate camera calibration for recovering 3D structure from images is a well-studied topic. Recently 3D vision tools for end-user applications have become popular among large audiences, mostly unskilled in computer vision. This motivates the need for a flexible and user-centric camera calibration method which drastically releases the critical requirements on the calibration target and ensures that low-quality or faulty images provided by end users do not degrade the overall calibration and in effect the resulting 3D model. In this paper we present and advocate an approach to camera calibration using fiducial markers, aiming at the accuracy of target calibration techniques without the requirement for a precise calibration pattern, to ease the calibration effort for the end-user. An extensive set of experiments with real images is presented which demonstrates improvements in the estimation of the parameters of the camera model as well as accuracy in the multi-view stereo reconstruction of large scale scenes. Pixel reprojection errors and ground truth errors obtained by our method are significantly lower compared to popular calibration routines, even though paper-printable and easy-to-use targets are employed.

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Incremental Surface Extraction From Sparse Structure-from-Motion Point Clouds
Christof Hoppe, Manfred Klopschitz, Michael Donoser, Horst Bischof. In Proceedings of the British Machine Vision Conference (BMVC), Bristol (UK), 2013.

BMVC 2013

Extracting surfaces from a sparse 3D point cloud in real-time can be beneficial for many applications that are based on Simultaneous Localization and Mapping~(SLAM) like occlusion handling or path planning. However, this is a complex task since the sparse point cloud is noisy, irregularly sampled and growing over time. In this paper, we propose a new method based on an optimal labeling of an incrementally reconstructed tetrahedralized point cloud. We propose a new sub-modular energy function that extracts the surfaces with the same accuracy as state-of-the-art with reduced computation time. Furthermore, our energy function can be easily adapted to additional 3D points and incrementally minimized using the dynamic graph cut in an efficient manner. In such a way, we are able to integrate several hundreds of 3D points per second while being largely independent from the overall scene size and therefore our novel method is suited for real-time SLAM applications.

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Incremental Line-based 3D Reconstruction using Geometric Constraints
Manuel Hofer, Andreas Wendel, Horst Bischof. In Proceedings of the British Machine Vision Conference (BMVC), Bristol (UK), 2013.

BMVC 2013

Generating accurate 3D models for man-made environments can be a challenging task due to the presence of texture-less objects or wiry structures. Since traditional point-based 3D reconstruction approaches may fail to integrate these structures into the resulting point cloud, a different feature representation is necessary. We present a novel approach which uses point features for camera estimation and additional line segments for 3D reconstruction. To avoid appearance-based line matching, we use purely geometric constraints for hypothesis generation and verification. Therefore, the proposed method is able to reconstruct both wiry structures as well as solid objects. The algorithm is designed to generate incremental results using online Structure-from-Motion and line-based 3D modelling in parallel. We show that the proposed method outperforms previous descriptor-less line matching approaches in terms of run-time while delivering accurate results.

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Probabilistic Range Image Integration for DSM and True-Orthophoto Generation
Markus Rumpler, Andreas Wendel, Horst Bischof. In Proceedings of the 18th Scandinavian Conference on Image Analysis (SCIA), Espoo (FI), 2013.

SCIA 2013

Typical photogrammetric processing pipelines for digital surface model (DSM) generation perform aerial triangulation, dense image matching and a fusion step to integrate multiple depth estimates into a consistent 2.5D surface model. The integration is strongly influenced by the quality of the individual depth estimates, which need to be handled robustly. We propose a probabilistically motivated 3D filtering scheme for range image integration. Our approach avoids a discrete voxel sampling, is memory efficient and can easily be parallelized. Neighborhood information given by a Delaunay triangulation can be exploited for photometric refinement of the fused DSMs before rendering true-orthophotos from the obtained models. We compare our range image fusion approach quantitatively on ground truth data by a comparison with standard median fusion. We show that our approach can handle a large amount of outliers very robustly and is able to produce improved DSMs and true-orthophotos in a qualitative comparison with current state-of-the-art commercial aerial image processing software.

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Line-based 3D Reconstruction of Wiry Objects
Manuel Hofer, Andreas Wendel, Horst Bischof. In Proceedings of the Computer Vision Winter Workshop (CVWW), Hernstein (Austria), 2013.

CVWW 2013

Man-made environments contain many weakly textured surfaces which are typically poorly modeled in sparse point reconstructions. Most notable, wiry structures such as fences, scaffolds, or power pylons are not contained at all. This paper presents a novel approach for generating line-based 3D models from image sequences. Initially, camera positions are obtained using conventional Structure-from-Motion techniques. In order to avoid explicit matching of 2D line segments in the various views we exploit the epipolar constraints and generate a series of 3D line hypotheses, which are then verified and clustered to obtain the final result. We show that this approach can be used to densify various sparse occupied point clouds of urban scenes in order to obtain a meaningful model of the underlying structure.

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Online Feedback for Structure-from-Motion Image Acquisition
Christof Hoppe, Manfred Klopschitz, Markus Rumpler, Andreas Wendel, Stefan Kluckner, Horst Bischof, Gerhard Reitmayr. In Proceedings of the British Machine Vision Conference (BMVC), Guildford, 2012. 

BMVC 2012

The quality and completeness of 3D models obtained by Structure-from-Motion (SfM) heavily depend on the image acquisition process. If the user gets feedback about the reconstruction quality already during the acquisition, he can optimize this process. We propose an online SfM approach that allows the inspection of the current reconstruction result on site. To guide the user throughout the acquisition, we visualize the current Ground Sampling Distance (GSD) and image redundancy as quality indicators on the surface model. The contributions of this paper are an online SfM framework for highresolution still images that achieves an accuracy close to an off-line SfM method and a visualization of quality measures that allow the user to optimize the image acquisition process. We compare the accuracy of the proposed online SfM to state-of-the-art batch-based SfM methods and demonstrate how our algorithm improves the acquisition process.

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Dense Reconstruction On-the-Fly
Andreas Wendel, Michael Maurer, Gottfried Graber, Thomas Pock, Horst Bischof. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Providence (USA), 2012.

CVPR 2012

We present a novel system that is capable of generating live dense volumetric reconstructions based on input from a micro aerial vehicle. The distributed reconstruction pipeline is based on state-of-the-art approaches to visual SLAM and variational depth map fusion, and is designed to exploit the individual capabilities of the system components. Results are visualized in real-time on a tablet interface, which gives the user the opportunity to interact. We demonstrate the performance of our approach by capturing several indoor and outdoor scenes on-the-fly and by evaluating our results with respect to a ground-truth model.

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Automatic Fusion of Partial Reconstructions
Andreas Wendel, Christof Hoppe, Horst Bischof, and Franz Leberl. In ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne (AU), 2012.

ISPRS 2012

Novel image acquisition tools such as micro aerial vehicles (MAVs) in form of quad- or octo-rotor helicopters support the creation of 3D reconstructions with ground sampling distances below 1 cm. The limitation of aerial photogrammetry to nadir and oblique views in heights of several hundred meters is bypassed, allowing close-up photos of facades and ground features. However, the new acquisition modality also introduces challenges: First, flight space might be restricted in urban areas, which leads to missing views for accurate 3D reconstruction and causes fracturing of large models. This could also happen due to vegetation or simply a change of illumination during image acquisition. Second, accurate geo-referencing of reconstructions is difficult because of shadowed GPS signals in urban areas, so alignment based on GPS information is often not possible.

In this paper, we address the automatic fusion of such partial reconstructions. Our approach is largely based on the work of (Wendel et al., 2011a), but does not require an overhead digital surface model for fusion. Instead, we exploit that patch-based semi-dense reconstruction of the fractured model typically results in several point clouds covering overlapping areas, even if sparse feature cor- respondences cannot be established. We approximate orthographic depth maps for the individual parts and iteratively align them in a global coordinate system. As a result, we are able to generate point clouds which are visually more appealing and serve as an ideal basis for further processing. Mismatches between parts of the fused models depend only on the individual point density, which allows us to achieve a fusion accuracy in the range of ±1 cm on our evaluation dataset.

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Efficient and Globally Optimal Multi View Dense Matching for Aerial Images
Arnold Irschara, Markus Rumpler, Philipp Meixner, Thomas Pock, Horst Bischof. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS), Melbourne (AU), 2012

ISPRS 2012

A variety of applications exist for aerial 3D reconstruction, ranging from the production of digital surface models (DSMs) and digital terrain models (DTMs) to the creation of true orthophoto and full 3D models of urban scenes that can be visualized through the web. In this paper we present an automated end-to-end workflow to create digital surface models from large scale and highly overlapping aerial images. The core component of our approach is a multi-view dense matching algorithm that fully exploits the redundancy of the data. This is in contrast to traditional two-view based stereo matching approaches in aerial photogrammetry. In particular, our solution to dense depth estimation is based on a multi-view plane sweep approach with discontinuity preserving global optimization. We provide a fully automatic framework for aerial triangulation, image overlap estimation and dense depth matching. Our algorithms are designed to run on current graphics processing units (GPUs) which makes large scale processing feasible at low cost. We present dense matching results from a large aerial survey comprising 3000 aerial images of Graz and give a detailed performance analysis in terms of accuracy and processing time.

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Photogrammetric Camera Network Design for Micro Aerial Vehicles
Christof Hoppe, Andreas Wendel, Stefanie Zollmann, Katrin Pirker, Arnold Irschara, Horst Bischof, Stefan Kluckner. In Proceedings of the Computer Vision Winter Workshop (CVWW), Mala Nedelja (Slovenia), 2012.

CVWW 2012

Micro Aerial Vehicles (MAVs) equipped with high resolution cameras have the ability of cost efficient and autonomous image acquisition from unconventional viewpoints. To fully exploit the limited flight-time of current MAVs view planning is essential for complete and precise 3D scene sampling. We propose a novel camera network design algorithm suitable for MAVs for close range photogrammetry that exploits prior knowledge of the surrounding. Our algorithm automatically determines a set of camera positions that guarantees important constraints for image based 3D reconstruction. On synthetic experiments we demonstrate that our camera network design obtains detailed 3D reconstructions with a reduced number of images at the desired accuracy level. Comparable results are also computed on an outdoor experiment using our MAV in autonomous flight mode.

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Efficient Structure from Motion with Weak Position and Orientation Priors
Arnold Irschara, Christof Hoppe, Horst Bischof, Stefan Kluckner. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Aerial Video Processing, 2011

CVPR 2011

In this paper we present an approach that leverages prior information from global positioning systems and inertial measurement units to speedup structure from motion computation. We propose a view selection strategy that advances vocabulary tree based coarse matching by also considering the geometric configuration between weakly oriented images. Furthermore, we introduce a fast and scalable reconstruction approach that relies on global rotation registration and robust bundle adjustment. Real world experiments are performed using data acquired by a micro aerial vehicle attached with GPS/INS sensors. Our proposed algorithm achieves orientation results that are sub-pixel accurate and the precision is on a par with results from incremental structure from motion approaches. Moreover, the method is scalable and computationally more efficient than previous approaches.

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Automatic Alignment of 3D Reconstructions using a Digital Surface Model
Andreas Wendel, Arnold Irschara, Horst Bischof. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Aerial Video Processing, 2011

CVPR 2011

We present a novel technique for the automatic alignment of Structure from Motion (SfM) models, acquired at ground level or by micro aerial vehicles, to an overhead Digital Surface Model (DSM) using GPS information. An additional refinement step based on the correlation of the DSM height map with the model height map corrects for the GPS localization uncertainties and results in precisely aligned models. Our approach successfully handles cases where previous methods had problems, including objects on the ground, unoccupied space, and models covering a small area. We present several applications of our approach, namely the fusion of detailed SfM model information into the original DSM, season-invariant matching using aligned models, and alignment for providing context in visualization.

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Multi-View Stereo: Redundancy Benefits for 3D Reconstruction
Markus Rumpler, Arnold Irschara, Horst Bischof. In Proceedings of the 35th Workshop of the Austrian Association for Pattern Recognition (AAPR/OAGM), Graz (Austria), 2011

CVWW 2012

This work investigates the influence of using multiple views for 3D reconstruction with respect to depth accuracy and robustness. In particular we show that multiview matching not only contributes to scene completeness, but also improves depth accuracy by improved triangulation angles. We first start by synthetic experiments on a typical aerial photogrammetric camera network and investigate how baseline (i.e. triangulation angle) and redundancy affect the depth error. Our evaluation also includes a comparison between combined pairwise triangulated and fused stereo pairs in contrast to true multiview triangulation. By analyzing the 3D uncertainty ellipsoid of triangulated points we demonstrate the clear advantage of a multiview approach over fused two view stereo algorithms. We propose an efficient dense matching algorithm that utilizes pairwise optical flow followed by a robust correspondence chaining approach. We provide evaluation results of the proposed method on ground truth data and compare its performance in contrast to a multiview plane sweep method.

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3D Vision Applications for MAVs: Localization and Reconstruction
Andreas Wendel, Michael Maurer, Arnold Irschara, Horst Bischof. In Proceedings of the International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), 2011

3DPVT 2011

This paper demonstrates our progress in integrating 3D computer vision applications, such as monocular localization and 3D reconstruction, on a micro aerial vehicle (MAV). We present an overview of algorithms used for the individual tasks, focused on the categorization in continuous and single-shot image acquisition, as well as online and offline processing. We propose to look for an application-specific trade-off and present some ideas how this could be achieved.

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Aerial Photogrammetry

 

Automated Photogrammetry for Three-Dimensional Models of Urban Spaces
Franz Leberl, Philipp Meixner, Andreas Wendel, Arnold Irschara. Optical Engineering, 51(2). SPIE, 2012.

Optical Engineering 2012

The location-aware Internet is inspiring intensive work addressing the automated assembly of three-dimensional models of urban spaces with their buildings, circulation spaces, vegetation, signs, even their above-ground and underground utility lines. Two-dimensional geographic information systems (GISs) and municipal utility information exist and can serve to guide the creation of models being built with aerial, sometimes satellite imagery, streetside images, indoor imaging, and alternatively with light detection and ranging systems (LiDARs) carried on airplanes, cars, or mounted on tripods. We review the results of current research to automate the information extraction from sensor data. We show that aerial photography at ground sampling distances (GSD) of 1 to 10 cm is well suited to provide geometry data about building facades and roofs, that streetside imagery at 0.5 to 2 cm is particularly interesting when it is collected within community photo collections (CPCs) by the general public, and that the transition to digital imaging has opened the no-cost option of highly overlapping images in support of a more complete and thus more economical automation. LiDAR-systems are a widely used source of three-dimensional data, but they deliver information not really superior to digital photography.

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Towards Fully Automatic Photogrammetric Reconstruction Using Digital Images Taken From UAVs
Arnold Irschara, Viktor Kaufmann, Manfred Klopschitz, Horst Bischof, Franz Leberl. Proceedings International Society for Photogrammetry and Remote Sensing Symposium, 100 Years ISPRS - Advancing Remote Sensing Science, 2010

ISPRS 2010

We argue that the future of remote sensing will see a diversification of sensors and sensor platforms. We argue further that remote sensing will also benefit from recent advances in computing technology to employ new algorithms previously too complex to apply. In this paper we support this argument by three demonstrations. First, we show that an unmanned aerial vehicle (UAV) equipped with digital cameras can provide valuable visual information about the Earth's surface rapidly and at low cost from nearly any viewpoint. Second, we demonstrate an end-to-end workflow to process a sizeable block of such imagery in a fully automated manner. Thirdly, we build this workflow on a novel computing system taking advantage of the invention of the Graphics Processing Unit (GPU) that is capable of performing complex algorithms in an acceptable elapsed time. The transition to diverse imaging sensors and platforms results in a requirement to deal with unordered sets of images, such as typically collected from a UAV, and to match and orientate these images automatically. Our approach is fully automated and capable of addressing large datasets in reasonable time and at low costs on a standard desktop PC. We compare our method to a semi-automatic orientation approach based on the PhotoModeler software and demonstrate superior performance in terms of automation, accuracy and processing time.

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Point Clouds: Lidar versus 3D Vision
Franz Leberl, Arnold Irschara, Thomas Pock, Michael Gruber, Susanne Scholz, Alexander Wiechert. Photogrammetric Engineering and Remote Sensing, 2010.

Lidar versus 3D Vision

Novel automated photogrammetry technologies are based on four innovations. First is the cost-free increase of overlaps between images when sensing is by digital means rather than film. Second is a vastly improved radiometric perfor- mance. Third is the transition towards multi-view matching and geometry. Fourth is the invention of the Graphics Processing Unit (GPU) that makes it possible to employ previously prohibitively complex algorithms for image matching. These innovations have led to an improved automation success of the photogrammetric workflow. Photogrammetry is therefore capable of producing point clouds at sub-pixel accuracy, at very dense point intervals and in near real-time, thereby eroding the traditional unique selling proposition of LiDAR scanners.

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