bluuebunny/crossref_metadata_2025 huggingface dataset:
USAGE OF MULTIPLE LIDAR SENSORS ON A MOBILE SYSTEM FOR THE DETECTION OF PERSONS WITH IMPLICIT SHAPE MODELS
Authors: Borgmann B. , Hebel M. , Arens M. , Stilla U.
Published: May 2018

Abstract. The focus of this paper is the processing of data from multiple LiDAR (light detection and ranging) sensors for the purpose of detecting persons in that data. Many LiDAR sensors (e.g., laser scanners) use a rotating scan head, which makes it difficult to properly timesynchronize multiple of such LiDAR sensors. An improper synchronization between LiDAR sensors causes temporal distortion effects if their data are directly merged. A merging of data is desired, since it could increase the data density and the perceived area. For the usage in person and object detection tasks, we present an alternative which circumvents the problem by performing the merging of multi-sensor data in the voting space of a method that is based on Implicit Shape Models (ISM). Our approach already assumes that there exist some uncertainties in the voting space. Therefore it is robust against additional uncertainties induced by temporal distortions. Unlike many existing approaches for object detection in 3D data, our approach does not rely on a segmentation step in the data preprocessing. We show that our merging of multi-sensor information in voting space has its advantages in comparison to a direct data merging, especially in situations with a lot of distortion effects.
MODULAR BUNDLE ADJUSTMENT FOR PHOTOGRAMMETRIC COMPUTATIONS
Authors: Börlin N. , Murtiyoso A. , Grussenmeyer P. , Menna F. , Nocerino E.
Published: May 2018

Abstract. In this paper we investigate how the residuals in bundle adjustment can be split into a composition of simple functions. According to the chain rule, the Jacobian (linearisation) of the residual can be formed as a product of the Jacobians of the individual steps. When implemented, this enables a modularisation of the computation of the bundle adjustment residuals and Jacobians where each component has limited responsibility. This enables simple replacement of components to e.g. implement different projection or rotation models by exchanging a module. The technique has previously been used to implement bundle adjustment in the open-source package DBAT (Börlin and Grussenmeyer, 2013) based on the Photogrammetric and Computer Vision interpretations of Brown (1971) lens distortion model. In this paper, we applied the technique to investigate how affine distortions can be used to model the projection of a tilt-shift lens. Two extended distortion models were implemented to test the hypothesis that the ordering of the affine and lens distortion steps can be changed to reduce the size of the residuals of a tilt-shift lens calibration. Results on synthetic data confirm that the ordering of the affine and lens distortion steps matter and is detectable by DBAT. However, when applied to a real camera calibration data set of a tilt-shift lens, no difference between the extended models was seen. This suggests that the tested hypothesis is false and that other effects need to be modelled to better explain the projection. The relatively low implementation effort that was needed to generate the models suggest that the technique can be used to investigate other novel projection models in photogrammetry, including modelling changes in the 3D geometry to better understand the tilt-shift lens.
MULTISPECTRAL AND PANCHROMATIC REGISTRATION OF ALSAT-2 IMAGES USING DENSE VECTOR MATCHING FOR PAN-SHARPENING PROCESS
Authors: Boukerch I. , Farhi N. , Karoui M. S. , Djerriri K. , Mahmoudi R.
Published: May 2018

Abstract. The pan-sharpening is a widely used operation in remote sensing image processing, this operation aims at combining an observable high spatial resolution panchromatic image with a multispectral one, to generate an unobservable image with the high spatial resolution of the former and a high spectral resolution of the latter. Generally, papers dealing with this problem omit the geometric part and suppose that these images are perfectly aligned, which is not necessarily the case for the raw imagery, where even the different bands in the multispectral imagery are misaligned. In this paper, new method for multispectral and panchromatic image registration is proposed to deal with the misalignment problem that reduces the pansharpening quality. This method called Dense Vector Matching (DVM) is based on the matching of a whole line-vector or column-vector from a reference band with the corresponding vector in a target band. DVM is applied on real data and has given acceptable results, where the QNR index of the pan-sharpening is better for images after band registration, also the registration error is reduced to sub-pixel using the proposed approach.
4D-SFM PHOTOGRAMMETRY FOR MONITORING SEDIMENT DYNAMICS IN A DEBRIS-FLOW CATCHMENT: SOFTWARE TESTING AND RESULTS COMPARISON
Authors: Cucchiaro S. , Maset E. , Fusiello A. , Cazorzi F.
Published: May 2018

Abstract. In recent years, the combination of Structure-from-Motion (SfM) algorithms and UAV-based aerial images has revolutionised 3D topographic surveys for natural environment monitoring, offering low-cost, fast and high quality data acquisition and processing. A continuous monitoring of the morphological changes through multi-temporal (4D) SfM surveys allows, e.g., to analyse the torrent dynamic also in complex topography environment like debris-flow catchments, provided that appropriate tools and procedures are employed in the data processing steps. In this work we test two different software packages (3DF Zephyr Aerial and Agisoft Photoscan) on a dataset composed of both UAV and terrestrial images acquired on a debris-flow reach (Moscardo torrent – North-eastern Italian Alps). Unlike other papers in the literature, we evaluate the results not only on the raw point clouds generated by the Structure-from- Motion and Multi-View Stereo algorithms, but also on the Digital Terrain Models (DTMs) created after post-processing. Outcomes show differences between the DTMs that can be considered irrelevant for the geomorphological phenomena under analysis. This study confirms that SfM photogrammetry can be a valuable tool for monitoring sediment dynamics, but accurate point cloud post-processing is required to reliably localize geomorphological changes.
IMPROVING SPHERICAL PHOTOGRAMMETRY USING 360° OMNI-CAMERAS: USE CASES AND NEW APPLICATIONS
Authors: Fangi G. , Pierdicca R. , Sturari M. , Malinverni E. S.
Published: May 2018

Abstract. During the last few years, there has been a growing exploitation of consumer-grade cameras allowing one to capture 360° images. Each device has different features and the choice should be entrusted on the use and the expected final output. The interest on such technology within the research community is related to its use versatility, enabling the user to capture the world with an omnidirectional view with just one shot. The potential is huge and the literature presents many use cases in several research domains, spanning from retail to construction, from tourism to immersive virtual reality solutions. However, the domain that could the most benefit is Cultural Heritage (CH), since these sensors are particularly suitable for documenting a real scene with architectural detail. Following the previous researches conducted by Fangi, which introduced its own methodology called Spherical Photogrammetry (SP), the aim of this paper is to present some tests conducted with the omni-camera Panono 360° which reach a final resolution comparable with a traditional camera and to validate, after almost ten years from the first experiment, its reliability for architectural surveying purposes. Tests have been conducted choosing as study cases Santa Maria della Piazza and San Francesco alle scale Churches in Ancona, Italy, since they were previously surveyed and documented with SP methodology. In this way, it has been possible to validate the accuracy of the new survey, performed by means an omni-camera, compared with the previous one for both outdoor and indoor scenario. The core idea behind this work is to validate if this new sensor can replace the standard image collection phase, speeding up the process, assuring at the same time the final accuracy of the survey. The experiment conducted demonstrate that, w.r.t. the SP methodology developed so far, the main advantage in using 360° omni-directional cameras lies on increasing the rapidity of acquisition and panorama creation phases. Moreover, in order to foresee the implications that a wide adoption of fast and agile tools of acquisition could bring within the CH domain, points cloud have been generated with the same panoramas and visualized in a WEB application, to allow a result dissemination between the users.
AUTOMATED SHAPE ANALYSIS OF TEETH FROM THE ARCHAELOGICAL SITE OF NERQIN NAVER
Authors: Gaboutchian A. , Simonyan H. , Knyaz V. , Petrosyan G. , Ter-Vardanyan L. , Leybova N. A. , Apresyan S. V.
Published: May 2018

Abstract. Traditional odontometry currently suggests a limited number of measurements on tooth coronal parts, including estimation of mesio-distal and vestibular-oral diameters, or dimension, through usually a single measurement of the maximal parameter. Taking into consideration the complexity, irregularity and variability of tooth shapes we find such measurements insufficient for interpreting tooth morphology. Thus we propose odontotomic approach of obtaining data from a series of parallel equally spaced sections in combination with automated detection of landmarks used for measurements. These sections allow locating maximal dimensions of teeth as well as collecting data from all parts of the tooth to describe it morphologically. Referring odontometric data to the whole tooth we obtain more precise and objective records which have proved to be informative in a series of dental and anthropological studies. Growing interest and implementing of digital technology in odontometric studies calls for studies ensuring transition to new methods. The current research is aimed to undertake a comparative study of the traditional and automated digital odontometry. The influence of various approaches to odontotomy (number and direction of sections) on odontometric data is subjected to studies as well. The above-mentioned tooth shape analysis is applied to samples from the archaeological site of Nerqin Naver to contribute to complicated odontological studies from the Early Bronze burials.
POSITION ACCURACY ANALYSIS OF A ROBUST VISION-BASED NAVIGATION
Authors: Gaglione S. , Del Pizzo S. , Troisi S. , Angrisano A.
Published: May 2018

Abstract. Using images to determine camera position and attitude is a consolidated method, very widespread for application like UAV navigation. In harsh environment, where GNSS could be degraded or denied, image-based positioning could represent a possible candidate for an integrated or alternative system. In this paper, such method is investigated using a system based on single camera and 3D maps. A robust estimation method is proposed in order to limit the effect of blunders or noisy measurements on position solution. The proposed approach is tested using images collected in an urban canyon, where GNSS positioning is very unaccurate. A previous photogrammetry survey has been performed to build the 3D model of tested area. The position accuracy analysis is performed and the effect of the robust method proposed is validated.
SINGLE-SHOT SEMANTIC MATCHER FOR UNSEEN OBJECT DETECTION
Authors: Gorbatsevich V. , Vizilter Y. , Knyaz V. , Moiseenko A.
Published: May 2018

Abstract. In this paper we combine the ideas of image matching, object detection, image retrieval and zero-shot learning for stating and solving the semantic matching problem. Semantic matcher takes two images (test and request) as input and returns detected objects (bounding boxes) on test image corresponding to semantic class represented by request (sample) image. We implement our single-shot semantic matcher CNN architecture based on GoogleNet and YOLO/DetectNet architectures. We propose the detection-by-request training and testing protocols for semantic matching algorithms. We train and test our CNN on the ILSVRC 2014 with 200 seen and 90 unseen classes and provide the real-time object detection with mAP 23 for seen and mAP 21 for unseen classes.
EVALUATION OF A TRAFFIC SIGN DETECTOR BY SYNTHETIC IMAGE DATA FOR ADVANCED DRIVER ASSISTANCE SYSTEMS
Authors: Hanel A. , Kreuzpaintner D. , Stilla U.
Published: May 2018

Abstract. Recently, several synthetic image datasets of street scenes have been published. These datasets contain various traffic signs and can therefore be used to train and test machine learning-based traffic sign detectors. In this contribution, selected datasets are compared regarding ther applicability for traffic sign detection. The comparison covers the process to produce the synthetic images and addresses the virtual worlds, needed to produce the synthetic images, and their environmental conditions. The comparison covers variations in the appearance of traffic signs and the labeling strategies used for the datasets, as well. A deep learning traffic sign detector is trained with multiple training datasets with different ratios between synthetic and real training samples to evaluate the synthetic SYNTHIA dataset. A test of the detector on real samples only has shown that an overall accuracy and ROC AUC of more than 95 % can be achieved for both a small rate of synthetic samples and a large rate of synthetic samples in the training dataset.
RECONSTRUCTION OF 3D MODELS FROM POINT CLOUDS WITH HYBRID REPRESENTATION
Authors: Hu P. , Dong Z. , Yuan P. , Liang F. , Yang B.
Published: May 2018

Abstract. The three-dimensional (3D) reconstruction of urban buildings from point clouds has long been an active topic in applications related to human activities. However, due to the structures significantly differ in terms of complexity, the task of 3D reconstruction remains a challenging issue especially for the freeform surfaces. In this paper, we present a new reconstruction algorithm which allows the 3D-models of building as a combination of regular structures and irregular surfaces, where the regular structures are parameterized plane primitives and the irregular surfaces are expressed as meshes. The extraction of irregular surfaces starts with an over-segmented method for the unstructured point data, a region growing approach based the adjacent graph of super-voxels is then applied to collapse these super-voxels, and the freeform surfaces can be clustered from the voxels filtered by a thickness threshold. To achieve these regular planar primitives, the remaining voxels with a larger flatness will be further divided into multiscale super-voxels as basic units, and the final segmented planes are enriched and refined in a mutually reinforcing manner under the framework of a global energy optimization. We have implemented the proposed algorithms and mainly tested on two point clouds that differ in point density and urban characteristic, and experimental results on complex building structures illustrated the efficacy of the proposed framework.
A GUIDED REGISTRATION STRATEGY EMPLOYING VIRTUAL PLANES TO OVERCOME NON-STANDARD GEOMETRIES – USING THE EXAMPLE OF MOBILE MAPPING AND AERIAL OBLIQUE IMAGERY
Authors: Jende P. , Nex F. , Gerke M. , Vosselman G.
Published: May 2018

Abstract. Mobile mapping (MM) is an intriguing as well as emerging platform and technology for geo-data acquisition. In typical areas of interest for MM campaigns, such as urban areas, unwanted GNSS multipath, non-line-of-sight effects, and IMU drifts may lead to deteriorated position fixes. In this work, we are proposing a novel technique to register MM and aerial oblique imagery. As aerial platforms are not affected by GNSS occlusions and are able to collect very-high resolution images, a co-registration of the data sets enables a) an independent verification of the platform’s accuracy and b) an adjustment of the MM data’s pose. Both data sets depict the scene from an entirely different perspective, which complicates the matching problem. Our approach is based on the assumption that common visible entities in both images are available, e.g. façade surfaces. By determining planes coinciding with these visible entities in object space, variances can be overcome. As the orientation of the data sets is known – MM data has an unknown accuracy – derived planes are employed to support a visibility hypothesis while storing image information for image registration in object space. This enables constraining search space to support the actual registration. Although the inhomogeneity of the data sets poses a challenge to a successful registration, we can show that our stepwise strategy of finding common visible entities, exploiting them to increase the resemblance of the data sets, and utilising accurate registration methods renders this matching scenario possible. In this paper, the algorithm is explained in detail, experimental results of significant steps will be shown, and possible extensions are discussed.
COMPARATIVE GEOMETRICAL ACCURACY INVESTIGATIONS OF HAND-HELD 3D SCANNING SYSTEMS – AN UPDATE
Authors: Kersten T. P. , Lindstaedt M. , Starosta D.
Published: May 2018

Abstract. Hand-held 3D scanning systems are increasingly available on the market from several system manufacturers. These systems are deployed for 3D recording of objects with different size in diverse applications, such as industrial reverse engineering, and documentation of museum exhibits etc. Typical measurement distances range from 0.5 m to 4.5 m. Although they are often easy-to-use, the geometric performance of these systems, especially the precision and accuracy, are not well known to many users. First geometrical investigations of a variety of diverse hand-held 3D scanning systems were already carried out by the Photogrammetry & Laser Scanning Lab of the HafenCity University Hamburg (HCU Hamburg) in cooperation with two other universities in 2016. To obtain more information about the accuracy behaviour of the latest generation of hand-held 3D scanning systems, HCU Hamburg conducted further comparative geometrical investigations using structured light systems with speckle pattern (Artec Spider, Mantis Vision PocketScan 3D, Mantis Vision F5-SR, Mantis Vision F5-B, and Mantis Vision F6), and photogrammetric systems (Creaform HandySCAN 700 and Shining FreeScan X7). In the framework of these comparative investigations geometrically stable reference bodies were used. The appropriate reference data was acquired by measurements with two structured light projection systems (AICON smartSCAN and GOM ATOS I 2M). The comprehensive test results of the different test scenarios are presented and critically discussed in this contribution.
MESH MODELLING OF 3D POINT CLOUD FROM UAV IMAGES BY POINT CLASSIFICATION AND GEOMETRIC CONSTRAINTS
Authors: Kim S. , Kim H. G. , Kim T.
Published: May 2018

Abstract. The point cloud generated by multiple image matching is classified as an unstructured point cloud because it is not regularly point spaced and has multiple viewpoints. The surface reconstruction technique is used to generate mesh model using unstructured point clouds. In the surface reconstruction process, it is important to calculate correct surface normals. The point cloud extracted from multi images contains position and color information of point as well as geometric information of images used in the step of point cloud generation. Thus, the surface normal estimation based on the geometric constraints is possible. However, there is a possibility that a direction of the surface normal is incorrectly estimated by noisy vertical area of the point cloud. In this paper, we propose an improved method to estimate surface normals of the vertical points within an unstructured point cloud. The proposed method detects the vertical points, adjust their normal vectors by analyzing surface normals of nearest neighbors. As a result, we have found almost all vertical points through point type classification, detected the points with wrong normal vectors and corrected the direction of the normal vectors. We compared the quality of mesh models generated with corrected surface normals and uncorrected surface normals. Result of comparison showed that our method could correct wrong surface normal successfully of vertical points and improve the quality of the mesh model.
EXPLOITING MIRRORS IN 3D RECONSTRUCTION OF SMALL ARTEFACTS
Authors: Kontogianni G. , Thomaidis A. T. , Chliverou R. , Georgopoulos A.
Published: May 2018

Abstract. 3D reconstruction of small artefacts is very significant in order to capture the details of the whole object irrespective of the documentation method which is used (Ranged Based or Image Based). Sometimes it is very difficult to achieve it because of hidden parts, occlusions, and obstructions which the object has. Hence, more data are necessary in order to 3D digitise the whole of the artefact leading to increased time for collecting and consequently processing the data. A methodology is necessary in order to reduce the collection of the data and therefore their processing time especially in cases of mass digitisation. So in this paper, the use of mirrors in particular high-quality mirrors in the data acquisition phase for the 3D reconstruction of small artefacts is investigated. Two case studies of 3D reconstruction are presented: the first one concerns Range-Based modelling especially a Time of Flight laser scanner is utilised and in the second one Image-Based modelling technique is implemented.
VERTICAL ACCURACY EVALUATION OF ASTER GDEM2 OVER A MOUNTAINOUS AREA BASED ON UAV PHOTOGRAMMETRY
Authors: Liang Y. , Qu Y. , Guo D. , Cui T.
Published: May 2018

Abstract. Global digital elevation models (GDEM) provide elementary information on heights of the Earth’s surface and objects on the ground. GDEMs have become an important data source for a range of applications. The vertical accuracy of a GDEM is critical for its applications. Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry are more convenient and more cost-effective. UAV photogrammetry produces the DEM of the survey area with high accuracy and high spatial resolution. As a result, DEMs resulted from UAV photogrammetry can be used for a more detailed and accurate evaluation of the GDEM product. This study investigates the vertical accuracy (in terms of elevation accuracy and systematic errors) of the ASTER GDEM Version 2 dataset over a complex terrain based on UAV photogrammetry. Experimental results show that the elevation errors of ASTER GDEM2 are in normal distribution and the systematic error is quite small. The accuracy of the ASTER GDEM2 coincides well with that reported by the ASTER validation team. The accuracy in the research area is negatively correlated to both the slope of the terrain and the number of stereo observations. This study also evaluates the vertical accuracy of the up-sampled ASTER GDEM2. Experimental results show that the accuracy of the up-sampled ASTER GDEM2 data in the research area is not significantly reduced by the complexity of the terrain. The fine-grained accuracy evaluation of the ASTER GDEM2 is informative for the GDEM-supported UAV photogrammetric applications.
3D MODELLING OF A HISTORICAL BUILDING USING CLOSE-RANGE PHOTOGRAMMETRY AND REMOTELY PILOTED AIRCRAFT SYSTEM (RPAS)
Authors: Lo Brutto M. , Ebolese D. , Dardanelli G.
Published: May 2018

Abstract. The photogrammetric survey of architectural Cultural Heritage is a very useful and standard process in order to obtain accurate 3D data for the documentation and visualization of historical buildings. In particular, the integration of terrestrial close-range photogrammetry and Remotely Piloted Aircraft Systems (RPASs) photogrammetry allows to create accurate and reliable 3D models of buildings and to monitor their state of conservation. The use of RPASs has indeed become more popular in Cultural Heritage survey to measure and detect areas that cannot normally be covered using terrestrial photogrammetry or terrestrial laser scanner. The paper presents the results of a photogrammetric survey executed to document the monumental complex of Villa Lampedusa ai Colli in Palermo (Italy), one of the most important historical buildings of the town. An integrated survey by close-range photogrammetry and RPAS photogrammetry was planned and carried out to reconstruct the 3D digital model of the monumental complex. Different images configurations (terrestrial, aerial nadiral, aerial parallel and oblique to the façades) have been acquired; data have been processed to verify the accuracy of the photogrammetric survey as regards the camera calibration parameters and the number of Ground Control Points (GCPs) measured on building façades. A very detailed 3D digital model and high-resolution ortho-images of the façades were obtained in order to carry out further analysis for historical studies, conservation and restoration project. The final 3D model of Villa Lampedusa ai Colli has been compared with a laser scanner 3D model to evaluate the quality of the photogrammetric approach. Beyond a purely metric assessment, 3D textured model has employed to generate 2D representations, useful for documentation purpose and to highlight the most significant damaged areas. 3D digital models and 2D representations can effectively contribute to monitor the state of conservation of historical buildings and become a very useful support for preliminary restoration works.
FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS
Authors: Maiwald F. , Schneider D. , Henze F. , Münster S. , Niebling F.
Published: May 2018

Abstract. This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB) in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images) difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings). It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.
INDOOR PHOTOGRAMMETRY AIDED WITH UWB NAVIGATION
Authors: Masiero A. , Fissore F. , Guarnieri A. , Vettore A.
Published: May 2018

Abstract. The subject of photogrammetric surveying with mobile devices, in particular smartphones, is becoming of significant interest in the research community. Nowadays, the process of providing 3D point clouds with photogrammetric procedures is well known. However, external information is still typically needed in order to move from the point cloud obtained from images to a 3D metric reconstruction. This paper investigates the integration of information provided by an UWB positioning system with visual based reconstruction to produce a metric reconstruction. Furthermore, the orientation (with respect to North-East directions) of the obtained model is assessed thanks to the use of inertial sensors included in the considered UWB devices. Results of this integration are shown on two case studies in indoor environments.
COMPARISON AND ASSESSMENT OF 3D REGISTRATION AND GEOREFERENCING APPROACHES OF POINT CLOUDS IN THE CASE OF EXTERIOR AND INTERIOR HERITAGE BUILDING RECORDING
Authors: Murtiyoso A. , Grussenmeyer P.
Published: May 2018

Abstract. In the field of 3D heritage documentation, point cloud registration is a relatively common issue. With rising needs for Historic Building Information Models (HBIMs), this issue has become more important as it determines the quality of the data to be used for HBIM modelling. Furthermore, in the context of historical buildings, it is often interesting to document both the exterior façades as well as the interior. This paper will discuss two approaches of the registration and georeferencing of building exterior and interior point clouds coming from different sensors, namely the independent georeferencing method and the free-network registration and georeferencing. Building openings (mainly windows) were used to establish common points between the systems. These two methods will be compared in terms of geometrical quality, while technical problems in performing them will also be discussed. Furthermore, an attempt to automate some parts of the workflow using automatic 3D keypoints and features detection and matching will also be described in the paper. Results show that while both approaches give similar results, the independent approach requires less work to perform. However, the free-network method has the advantage of being able to compensate for any systematic georeferencing error on either system. As regards to the automation attempt, the use of 3D keypoints and features may reduce processing time; however correct tie point correspondence filtering remains difficult in the presence of heavy point cloud noise.
STOCHASTIC SURFACE MESH RECONSTRUCTION
Authors: Ozendi M. , Akca D. , Topan H.
Published: May 2018

Abstract. 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.
THE ESTIMATION OF PRECISIONS IN THE PLANNING OF UAS PHOTOGRAMMETRIC SURVEYS
Authors: Passoni D. , Federici B. , Ferrando I. , Gagliolo S. , Sguerso D.
Published: May 2018

Abstract. The Unmanned Aerial System (UAS) is widely used in the photogrammetric surveys both of structures and of small areas. Geomatics focuses the attention on the metric quality of the final products of the survey, creating several 3D modelling applications from UAS images. As widely known, the quality of results derives from the quality of images acquisition phase, which needs an a priori estimation of the expected precisions. The planning phase is typically managed using dedicated tools, adapted from the traditional aerial-photogrammetric flight plan. But UAS flight has features completely different from the traditional one. Hence, the use of UAS for photogrammetric applications today requires a growth in knowledge in planning. The basic idea of this research is to provide a drone photogrammetric flight planning tools considering the required metric precisions, given a priori the classical parameters of a photogrammetric planning: flight altitude, overlaps and geometric parameters of the camera. The created “office suite” allows a realistic planning of a photogrammetric survey, starting from an approximate knowledge of the Digital Surface Model (DSM), and the effective attitude parameters, changing along the route. The planning products are the overlapping of the images, the Ground Sample Distance (GSD) and the precision on each pixel taking into account the real geometry. The different tested procedures, the obtained results and the solution proposed for the a priori estimates of the precisions in the particular case of UAS surveys are here reported.
A COMPARISON OF TWO STRATEGIES FOR AVOIDING NEGATIVE TRANSFER IN DOMAIN ADAPTATION BASED ON LOGISTIC REGRESSION
Authors: Paul A. , Vogt K. , Rottensteiner F. , Ostermann J. , Heipke C.
Published: May 2018

Abstract. In this paper we deal with the problem of measuring the similarity between training and tests datasets in the context of transfer learning (TL) for image classification. TL tries to transfer knowledge from a source domain, where labelled training samples are abundant but the data may follow a different distribution, to a target domain, where labelled training samples are scarce or even unavailable, assuming that the domains are related. Thus, the requirements w.r.t. the availability of labelled training samples in the target domain are reduced. In particular, if no labelled target data are available, it is inherently difficult to find a robust measure of relatedness between the source and target domains. This is of crucial importance for the performance of TL, because the knowledge transfer between unrelated data may lead to negative transfer, i.e. to a decrease of classification performance after transfer. We address the problem of measuring the relatedness between source and target datasets and investigate three different strategies to predict and, consequently, to avoid negative transfer in this paper. The first strategy is based on circular validation. The second strategy relies on the Maximum Mean Discrepancy (MMD) similarity metric, whereas the third one is an extension of MMD which incorporates the knowledge about the class labels in the source domain. Our method is evaluated using two different benchmark datasets. The experiments highlight the strengths and weaknesses of the investigated methods. We also show that it is possible to reduce the amount of negative transfer using these strategies for a TL method and to generate a consistent performance improvement over the whole dataset.
ARCHAEOLOGICAL FEATURE DETECTION FROM ARCHIVE AERIAL PHOTOGRAPHY WITH A SFM-MVS AND IMAGE ENHANCEMENT PIPELINE
Authors: Peppa M. V. , Mills J. P. , Fieber K. D. , Haynes I. , Turner S. , Turner A. , Douglas M. , Bryan P. G.
Published: May 2018

Abstract. Understanding and protecting cultural heritage involves the detection and long-term documentation of archaeological remains alongside the spatio-temporal analysis of their landscape evolution. Archive aerial photography can illuminate traces of ancient features which typically appear with different brightness values from their surrounding environment, but are not always well defined. This research investigates the implementation of the Structure-from-Motion - Multi-View Stereo image matching approach with an image enhancement algorithm to derive three epochs of orthomosaics and digital surface models from visible and near infrared historic aerial photography. The enhancement algorithm uses decorrelation stretching to improve the contrast of the orthomosaics so as archaeological features are better detected. Results include 2D / 3D locations of detected archaeological traces stored into a geodatabase for further archaeological interpretation and correlation with benchmark observations. The study also discusses the merits and difficulties of the process involved. This research is based on a European-wide project, entitled “Cultural Heritage Through Time”, and the case study research was carried out as a component of the project in the UK.
CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS
Authors: Pilarska M.
Published: May 2018

Abstract. Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.
REPRESENTING ROAD RELATED LASERSCANNED DATA IN CURVED REGULAR GRID: A SUPPORT TO AUTONOMOUS VEHICLES
Authors: Potó V. , Csepinszky A. , Barsi Á.
Published: May 2018

Abstract. The terrestrial and mobile laser scanning has become nowadays a mature technology applied in several technical and non-technical applications. The transportation infrastructure can be surveyed by these technologies in an excellent way, then 3D maps, fly-through videos and road furniture inventories can be derived among many other applications. The very detailed measurement and the realistic feature enable even to be used in games or simulators. This advantage was to be analyzed in vehicular simulation environment; the primary goal of the paper was to demonstrate a potential workflow and use case for such laser scanning data. The selected simulation package was the OpenCRG, which is being a component of OpenDRIVE-OpenCRG-OpenSCENARIO system, where it has been developed for microscopic simulations, e.g. vibrations, tire models or vehicle suspension systems. Because of the realistic visualization of CRG models it is very popular in the design and development of autonomous vehicles. The paper presents two different paved pilot sites surveyed by these technologies, then the raw data preparation is described and the details of the CRG model building is shown. The results of the experiments bring an overview, how the captured field data can be represented and interpreted in road surface context. The diagrams illustrate the potential of the very high resolution (1 cm) model, which allows to identify each separate cobble stone or to study surface roughness.
LOW-COST 3D DEVICES AND LASER SCANNERS COMPARISON FOR THE APPLICATION IN ORTHOPEDIC CENTRES
Authors: Redaelli D. F. , Gonizzi Barsanti S. , Fraschini P. , Biffi E. , Colombo G.
Published: May 2018

Abstract. Low-cost 3D sensors are nowadays widely diffused and many different solutions are available on the market. Some of these devices were developed for entertaining purposes, but are used also for acquisition and processing of different 3D data with the aim of documentation, research and study. Given the fact that these sensors were not developed for this purpose, it is necessary to evaluate their use in the capturing process. This paper shows a preliminary research comparing the Kinect 1 and 2 by Microsoft, the Structure Sensor by Occipital and the O&P Scan by Rodin4D in a medical scenario (i.e. human body scans). In particular, these sensors were compared to Minolta Vivid 9i, chosen as reference because of its higher accuracy. Different test objects were analysed: a calibrated flat plane, for the evaluation of the systematic distance error for each device, and three different parts of a mannequin, used as samples of human body parts. The results showed that the use of a certified flat plane is a good starting point in characterizing the sensors, but a complete analysis with objects similar to the ones of the real context of application is required. For example, the Kinect 2 presented the best results among the low-cost sensors on the flat plane, while the Structure Sensor was more reliable on the mannequin parts.
COMPARISON BETWEEN RGB AND RGB-D CAMERAS FOR SUPPORTING LOW-COST GNSS URBAN NAVIGATION
Authors: Rossi L. , De Gaetani C. I. , Pagliari D. , Realini E. , Reguzzoni M. , Pinto L.
Published: May 2018

Abstract. A pure GNSS navigation is often unreliable in urban areas because of the presence of obstructions, thus preventing a correct reception of the satellite signal. The bridging between GNSS outages, as well as the vehicle attitude reconstruction, can be recovered by using complementary information, such as visual data acquired by RGB-D or RGB cameras. In this work, the possibility of integrating low-cost GNSS and visual data by means of an extended Kalman filter has been investigated. The focus is on the comparison between the use of RGB-D or RGB cameras. In particular, a Microsoft Kinect device (second generation) and a mirrorless Canon EOS M RGB camera have been compared. The former is an interesting RGB-D camera because of its low-cost, easiness of use and raw data accessibility. The latter has been selected for the high-quality of the acquired images and for the possibility of mounting fixed focal length lenses with a lower weight and cost with respect to a reflex camera. The designed extended Kalman filter takes as input the GNSS-only trajectory and the relative orientation between subsequent pairs of images. Depending on the visual data acquisition system, the filter is different because RGB-D cameras acquire both RGB and depth data, allowing to solve the scale problem, which is instead typical of image-only solutions. The two systems and filtering approaches were assessed by ad-hoc experimental tests, showing that the use of a Kinect device for supporting a u-blox low-cost receiver led to a trajectory with a decimeter accuracy, that is 15 % better than the one obtained when using the Canon EOS M camera.
Is Your Kidney for Sale? An Economic and Policy Perspective on the Legalization of a Living Kidney Vendor Program in the United States
Authors: Kuenzli Kristine D.
Published: May 2018

The National Organ Transplant Act of 1984 (hereinafter NOTA) was an attempt to regulate, streamline, and encourage legal organ donation. NOTA has undergone some amendments since its enactment, including attempts to modernize the registry process and create a unified donation and transplant network. However, the regulation on the sale of organs has remained steadfast. We continue to have an organ shortage, and the statistics on the number of individuals dying each day awaiting transplants is only getting worse. An additional amendment to NOTA is necessary to solve our organ donation crisis. This Article identifies the relevant NOTA provisions, identifies some significant court decisions, and explores the policy and economic arguments in support of and against creating a living organ trade in the United States. In addition, this Article explains the Iranian Living- Unrelated donor program, and the government regulations necessary to create a living kidney vendor program in the United States.
Overcoming Creditor Misfortune Creatively: Structured Dismissals in Chapter 11 Bankruptcies
Authors: Allegretto Alessandra
Published: May 2018

No Abstract.
Turberas y deforestación: la evolución del paisaje a través de las fuentes documentales (Bonales de Puebla de Don Rodrigo, Ciudad Real)
Authors: Fidalgo Hijano Concepción , González Martín Juan Antonio , García Gimenez Rosario , Arteaga Cardineau Carlos , Colmenero María Luisa
Published: May 2018

El entorno de Puebla de Don Rodrigo (Ciudad Real) constituye una de las zonas de mayor interés paisajístico del interior de la Península Ibérica debido, entre otras razones, a la presencia de un conjunto de turberas ácidas de reducida extensión, denominadas localmente “bonales”. El presente trabajo se centra en el análisis de las singulares características del paisaje de este territorio, esencialmente desde el siglo XVI. El conocimiento de las condiciones imperantes en aquellos momentos, algunos de los cuales se corresponden con etapas álgidas de la denominada Pequeña Edad del Hielo, permitirá iluminar la evolución experimentada por estos humedales hasta el momento actual, infiriendo que una intensa y secular deforestación es responsable de la génesis de las transformaciones del medio, y en concreto del desarrollo de los encharcamientos que ha permitido la aparición de estos humedales higroturbosos de enorme valor natural.
Aproximación a los entornos peatonales a través de una encuesta a la población: aplicación a la ciudad de Granada
Authors: Talavera-García Rubén , Valenzuela-Montes Luis M.
Published: May 2018

La movilidad peatonal está siendo cada vez más importante por su vinculación con la idea de ciudades sostenibles. En este punto, es crucial entender las actitudes y percepciones que los peatones tienen respecto a caminar y respecto al entorno urbano. En el presente trabajo se lleva a cabo un análisis cuantitativo y global de los entornos de movilidad peatonal, basado en la información obtenida a través de una encuesta que incluye cuestiones agrupadas en diferentes áreas temáticas concernientes a la movilidad peatonal en la ciudad de Granada. Los resultados obtenidos ponen de manifiesto la actitud positiva de la población respecto a caminar, así como el hecho de que bulevares y calles comerciales son las tipologías de calle de mayor preferencia por parte de la población. Un enfoque integral, basado en la encuesta, permite enriquecer la planificación de la movilidad local considerando mejoras en los entornos peatonales.
Comercio minorista y peatonalización: evolución y adaptación en la ciudad costera de Malgrat de Mar (Barcelona)
Authors: Simó López Meritxell , Casellas Antònia , Avellaneda Pau
Published: May 2018

La desaparición del comercio minorista del centro urbano es uno de los principales problemas que afecta a las ciudades del siglo XXI. El presente trabajo analiza la evolución de este tipo de comercio en zonas comerciales centrales vinculándolo a los efectos de la peatonalización y al cambio de ciclo económico en Malgrat de Mar, una ciudad costera de la provincia de Barcelona. Con una metodología cualitativa basada en entrevistas semi-estructuradas y el análisis de datos socio-económicos y documentos de planificación urbanística se estudian los factores que influyen en el cierre de establecimientos y el cambio de actividades comerciales durante el período 2007-2015. Los resultados indican que, contrariamente a la opinión generalizada de la población local, la rehabilitación urbanística y la estrategia de peatonalización impulsada por el Ayuntamiento han contribuido a mantener la viabilidad de los comercios minoristas. Otros factores positivos identificados son la adaptación y especialización de los comercios a los nuevos hábitos de consumo.
Does Inward Foreign Direct Investment Promote Export? Empirical Evidence from Sri Lanka
Authors: NPG Samantha , Haiyun Liu
Published: May 2018

Export-led growth hypothesis assumed that long-term economic growth can be achieved through higher exports. Foreign Direct Investment (FDI) is one of the determinants of export performance that can have a substitute effect or complementary relationship to export. The aim of this study is to investigate the impact of inward FDI on the export performance of Sri Lanka during the period from 1980 to 2016. Auto Regressive Distributed Lag (ARDL) model and bound test are applied to identify the long-run relationship and short-run dynamics of the selected variables. The short-run causality is checked by applying the Granger causality test. The ARDL bound test confirms long-run relationship among the variables. The study finds positive insignificant long run and short-run relationships between FDI and exports in Sri Lanka for the data period. Exports are highly sensitive to GDP and real effective exchange rate in the short-run and to domestic investment in the long-run. In order to promote exports via FDI, government policy should focus on attracting more FDI by drawing attention to national competitiveness. The study suggests a comprehensive sector level investigation on the impact of FDI on export performance of Sri Lanka.