bluuebunny/crossref_metadata_2025 huggingface dataset:
3D VIRTUAL CH INTERACTIVE INFORMATION SYSTEMS FOR A SMART WEB BROWSING EXPERIENCE FOR DESKTOP PCS AND MOBILE DEVICES
Authors: Scianna A. , La Guardia M.
Published: May 2018

Abstract. Recently, the diffusion of knowledge on Cultural Heritage (CH) has become an element of primary importance for its valorization. At the same time, the diffusion of surveys based on UAV Unmanned Aerial Vehicles (UAV) technologies and new methods of photogrammetric reconstruction have opened new possibilities for 3D CH representation. Furthermore the recent development of faster and more stable internet connections leads people to increase the use of mobile devices. In the light of all this, the importance of the development of Virtual Reality (VR) environments applied to CH is strategic for the diffusion of knowledge in a smart solution. In particular, the present work shows how, starting from a basic survey and the further photogrammetric reconstruction of a cultural good, is possible to built a 3D CH interactive information system useful for desktop and mobile devices. For this experimentation the Arab-Norman church of the Trinity of Delia (in Castelvetrano-Sicily-Italy) has been adopted as case study. The survey operations have been carried out considering different rapid methods of acquisition (UAV camera, SLR camera and smartphone camera). The web platform to publish the 3D information has been built using HTML5 markup language and WebGL JavaScript libraries (Three.js libraries). This work presents the construction of a 3D navigation system for a web-browsing of a virtual CH environment, with the integration of first person controls and 3D popup links. This contribution adds a further step to enrich the possibilities of open-source technologies applied to the world of CH valorization on web.
3D COMPARISON TOWARDS A COMPREHENSIVE ANALYSIS OF A BUILDING IN CULTURAL HERITAGE
Authors: Selvaggi I. , Dellapasqua M. , Franci F. , Spangher A. , Visintini D. , Bitelli G.
Published: May 2018

Abstract. Terrestrial remote sensing techniques, including both Terrestrial Laser Scanning (TLS) and Close-Range Photogrammetry (CRP), have been recently used in multiple applications and projects with particular reference to the documentation/inspection of a wide variety of Cultural Heritage structures. The high density of TLS point cloud data allows to perform structure survey in an unprecedented level of detail, providing a direct solution for the digital three-dimensional modelling, the site restoration and the analysis of the structural conditions. Textural information provided by CRP can be used for the photorealistic representation of the surveyed structure. With respect to many studies, the combination of TLS and CRP techniques produces the best results for Cultural Heritage documentation purposes. Moreover, TLS and CRP point cloud data have been proved to be useful in the field of deformation analysis and structural health monitoring. They can be the input data for the Finite Element Method (FEM), providing some prior knowledge concerning the material and the boundary conditions such as constraints and loading. The paper investigates the capabilities and advantages of TLS and CRP data integration for the three-dimensional modelling compared to a simplified geometric reconstruction. This work presents some results concerning the Baptistery of Aquileia in Italy, characterized by an octagonal plan and walls composed by masonry stones with good texture.
APPLICATION OF MLS DATA TO THE ASSESSMENT OF SAFETY-RELATED FEATURES IN THE SURROUNDING AREA OF AUTOMATICALLY DETECTED PEDESTRIAN CROSSINGS
Authors: Soilán M. , Riveiro B. , Sánchez-Rodríguez A. , González-deSantos L. M.
Published: May 2018

Abstract. During the last few years, there has been a huge methodological development regarding the automatic processing of 3D point cloud data acquired by both terrestrial and aerial mobile mapping systems, motivated by the improvement of surveying technologies and hardware performance. This paper presents a methodology that, in a first place, extracts geometric and semantic information regarding the road markings within the surveyed area from Mobile Laser Scanning (MLS) data, and then employs it to isolate street areas where pedestrian crossings are found and, therefore, pedestrians are more likely to cross the road. Then, different safety-related features can be extracted in order to offer information about the adequacy of the pedestrian crossing regarding its safety, which can be displayed in a Geographical Information System (GIS) layer. These features are defined in four different processing modules: Accessibility analysis, traffic lights classification, traffic signs classification, and visibility analysis. The validation of the proposed methodology has been carried out in two different cities in the northwest of Spain, obtaining both quantitative and qualitative results for pedestrian crossing classification and for each processing module of the safety assessment on pedestrian crossing environments.
VALIDATING A WORKFLOW FOR TREE INVENTORY UPDATING WITH 3D POINT CLOUDS OBTAINED BY MOBILE LASER SCANNING
Authors: Wang J. , Lindenbergh R.
Published: May 2018

Abstract. Urban trees are an important component of our environment and ecosystem. Trees are able to combat climate change, clean the air and cool the streets and city. Tree inventory and monitoring are of great interest for biomass estimation and change monitoring. Conventionally, parameters of trees are manually measured and documented in situ, which is not efficient regarding labour and costs. Light Detection And Ranging (LiDAR) has become a well-established surveying technique for the acquisition of geo-spatial information. Combined with automatic point cloud processing techniques, this in principle enables the efficient extraction of geometric tree parameters. In recent years, studies have investigated to what extend it is possible to perform tree inventories using laser scanning point clouds. Give the availability of a city of Delft Open data tree repository, we are now able to present, validate and extend a workflow to automatically obtain tree data from tree location until tree species. The results of a test over 47 trees show that the proposed methods in the workflow are able to individual urban trees. The tree species classification results based on the extracted tree parameters show that only one tree was wrongly classified using k-means clustering.
FROM A POINT CLOUD SURVEY TO A MASS 3D MODELLING: RENAISSANCE HBIM IN POGGIO A CAIANO
Authors: Bolognesi C. , Garagnani S.
Published: May 2018

Abstract. This paper introduces some studies developed regarding the Medicea Villa at Poggio a Caiano, in Italy. The monumental building was built by Lorenzo de’ Medici and his heirs following the design of the famous architect Giuliano da Sangallo, between 1485 and 1520. The Villa embodies many of the typical features of the Italian Renaissance, added a monumental double circular stairway in the front façade during neoclassical times, heading to the upper balcony surrounded by a balustrade. The Villa was surveyed taking advantage of Terrestrial Laser Scanning and Digital Photogrammetry, in order to produce a detailed model to be translated into a HBIM digital prototype then. The Scan-to-BIM approach was obtained with a generation of semantics and components proper of Sangallo’s architectural grammar, first of all defining the object, then geometry, and then their parametrization. This process led to a model of the exteriors, used to better understand the architectural composition of the volumes, to make some hypothesis on its shape according to the original architect’s drawing in the Taccuino Senese, on its general structural behaviours, to understand the limits of a process and the perspective of a research that goes from a digital survey to the HBIM environment.
DEVELOPMENT OF A SINGLE-VIEW ODOMETER BASED ON PHOTOGRAMMETRIC BUNDLE ADJUSTMENT
Authors: Yoon S. J. , Yoon W. S. , Jung J. W. , Kim T.
Published: May 2018

Abstract. Recently, a vehicle is equipped with various sensors, which aim smart and autonomous functions. Single-view odometer estimates its pose using a monoscopic camera mounted on a vehicle. It was generally studied in the field of computer vision. On the other hands, photogrammetry focuses to produce precise three-dimensional position information using bundle adjustment methods. Therefore, this paper proposes to apply photogrammetric approach to single view odometer. Firstly, it performs real-time corresponding point extraction. Next, it estimates the pose using relative orientation based on coplanarity conditions. Then, scale calibration is performed to convert the estimated translation in the model space to the translation in the real space. Finally, absolute orientation is performed using more than three images. In this step, we also extract the appropriate model points through verification procedure. For experiments, we used the data provided by KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) community. This technique took 0.12 seconds of processing time per frame. The rotation estimation error was about 0.005 degree per meter and the translation estimation error was about 6.8 %. The results of this study have shown the applicability of photogrammetry to visual odometry technology.
3D BUILDING CHANGE DETECTION BETWEEN CURRENT VHR IMAGES AND PAST LIDAR DATA
Authors: Zhou K. , Gorte B. , Lindenbergh R. , Widyaningrum E.
Published: May 2018

Abstract. Change detection is an essential step to locate the area where an old model should be updated. With high density and accuracy, LiDAR data is often used to create a 3D city model. However, updating LiDAR data at state or nation level often takes years. Very high resolution (VHR) images with high updating rate is therefore an option for change detection. This paper provides a novel and efficient approach to derive pixel-based building change detection between past LiDAR and new VHR images. The proposed approach aims notably at reducing false alarms of changes near edges. For this purpose, LiDAR data is used to supervise the process of finding stereo pairs and derive the changes directly. This paper proposes to derive three possible heights (so three DSMs) by exploiting planar segments from LiDAR data. Near edges, the up to three possible heights are transformed into discrete disparities. A optimal disparity is selected from a reasonable and computational efficient range centered on them. If the optimal disparity is selected, but still the stereo pair found is wrong, a change has been found. A Markov random field (MRF) with built-in edge awareness from images is designed to find optimal disparity. By segmenting the pixels into plane and edge segments, the global optimization problem is split into many local ones which makes the optimization very efficient. Using an optimization and a consecutive occlusion consistency check, the changes are derived from stereo pairs having high color difference. The algorithm is tested to find changes in an urban areas in the city of Amersfoort, the Netherlands. The two different test cases show that the algorithm is indeed efficient. The optimized disparity images have sharp edges along those of images and false alarms of changes near or on edges and occlusions are largely reduced.
GRAPHICS-IMAGE MIXED METHOD FOR LARGE-SCALE BUILDINGS RENDERING
Authors: Zhou Y. , Xu Q. , Xing S. , Hu X.
Published: May 2018

Abstract. Urban 3D model data is huge and unstructured, LOD and Out-of-core algorithm are usually used to reduce the amount of data that drawn in each frame to improve the rendering efficiency. When the scene is large enough, even the complex optimization algorithm is difficult to achieve better results. Based on the traditional study, a novel idea was developed. We propose a graphics and image mixed method for large-scale buildings rendering. Firstly, the view field is divided into several regions, the graphics-image mixed method used to render the scene on both screen and FBO, then blending the FBO with scree. The algorithm is tested on the huge CityGML model data in the urban areas of New York which contained 188195 public building models, and compared with the Cesium platform. The experiment result shows the system was running smoothly. The experimental results confirm that the algorithm can achieve more massive building scene roaming under the same hardware conditions, and can rendering the scene without vision loss.
SENSOR- AND SCENE-GUIDED INTEGRATION OF TLS AND PHOTOGRAMMETRIC POINT CLOUDS FOR LANDSLIDE MONITORING
Authors: Zieher T. , Toschi I. , Remondino F. , Rutzinger M. , Kofler Ch. , Mejia-Aguilar A. , Schlögel R.
Published: May 2018

Abstract. Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor’s data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.
INFLUENCE OF DOMAIN SHIFT FACTORS ON DEEP SEGMENTATION OF THE DRIVABLE PATH OF AN AUTONOMOUS VEHICLE
Authors: Bormans R. P. A. , Lindenbergh R. C. , Karimi Nejadasl F.
Published: May 2018

Abstract. One of the biggest challenges for an autonomous vehicle (and hence the WEpod) is to see the world as humans would see it. This understanding is the base for a successful and reliable future of autonomous vehicles. Real-world data and semantic segmentation generally are used to achieve full understanding of its surroundings. However, deploying a pretrained segmentation network to a new, previously unseen domain will not attain similar performance as it would on the domain where it is trained on due to the differences between the domains. Although research is done concerning the mitigation of this domain shift, the factors that cause these differences are not yet fully explored. We filled this gap with the investigation of several factors. A base network was created by a two-step finetuning procedure on a convolutional neural network (SegNet) which is pretrained on CityScapes (a dataset for semantic segmentation). The first tuning step is based on RobotCar (road scenery dataset recorded in Oxford, UK) while afterwards this network is fine-tuned for a second time but now on the KITTI (road scenery dataset recorded in Germany) dataset. With this base, experiments are used to obtain the importance of factors such as horizon line, colour and training order for a successful domain adaptation. In this case the domain adaptation is from the KITTI and RobotCar domain to the WEpod domain. For evaluation, groundtruth labels are created in a weakly-supervised setting. Negative influence was obtained for training on greyscale images instead of RGB images. This resulted in drops of IoU values up to 23.9 % for WEpod test images. The training order is a main contributor for domain adaptation with an increase in IoU of 4.7 %. This shows that the target domain (WEpod) is more closely related to RobotCar than to KITTI.
RESPONSIVE URBAN MODELS BY PROCESSING SETS OF HETEROGENEOUS DATA
Authors: Calvano M. , Casale A. , Ippoliti E. , Guadagnoli F.
Published: May 2018

Abstract. This paper presents some steps in experimentation aimed at describing urban spaces made following the series of earthquakes that affected a vast area of central Italy starting on 24 August 2016. More specifically, these spaces pertain to historical centres of limited size and case studies that can be called “problematic” (due to complex morphological and settlement conditions, because they are difficult to access, or because they have been affected by calamitous events, etc.). The main objectives were to verify the use of sets of heterogeneous data that are already largely available to define a workflow and develop procedures that would allow some of the steps to be automated as much as possible. The most general goal was to use the experimentation to define a methodology to approach the problem aimed at developing descriptive responsive models of the urban space, that is, morphological and computer-based models capable of being modified in relation to the constantly updated flow of input data.
A NEW PROTOCOL FOR TEXTURE MAPPING PROCESS AND 2D REPRESENTATION OF RUPESTRIAN ARCHITECTURE
Authors: Carnevali L. , Carpiceci M. , Angelini A.
Published: May 2018

Abstract. The development of the survey techniques for architecture and archaeology requires a general review in the methods used for the representation of numerical data. The possibilities offered by data processing allow to find new paths for studying issues connected to the drawing discipline. The research project aimed at experimenting different approaches for the representation of the rupestrian architecture and the texture mapping process. The nature of the rupestrian architecture does not allow a traditional representation of sections and projections of edges and outlines. The paper presents a method, the Equidistant Multiple Sections (EMS), inspired by cartography and based on the use of isohipses generated from different geometric plane. A specific paragraph is dedicated to the texture mapping process for unstructured surface models. One of the main difficulty in the image projection consists in the recognition of homologous points between image and point cloud, above all in the areas with most deformations. With the aid of the “virtual scan” tool a different procedure was developed for improving the correspondences of the image. The result show a sensible improvement of the entire process above all for the architectural vaults. A detailed study concerned the unfolding of the straight line surfaces; the barrel vault of the analyzed chapel has been unfolded for observing the paintings in the real shapes out of the morphological context.
IMPROVING IMAGE MATCHING BY REDUCING SURFACE REFLECTIONS USING POLARISING FILTER TECHNIQUES
Authors: Conen N. , Hastedt H. , Kahmen O. , Luhmann T.
Published: May 2018

Abstract. In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud. To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results. However, the filter may influence the camera’s orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002) using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (Δc ≤ 4 μm) with the polarising filter in use. Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.
ANCIENT SHIPYARD ON TURKEY’S DANA ISLAND: ITS 3D MODELLING WITH PHOTOGRAMMETRY AND COMPUTER GRAPHICS
Authors: Denker A. , Oniz H.
Published: May 2018

Abstract. Although a small island 2 km off the southern coast of Turkey, Dana Island offers a rich history which is likely to shed light upon the Dark Ages. Starting from 2015 our archaeological team discovered through continuing coastal and underwater excavations 274 shipsheds/slipways there. This discovery places Dana Island among the biggest shipyards of antiquity. The slipways varied in dimensions suitable for vessels of different sizes from small boats to large warships. Historical sources suggest that the name of the island may stem from Yadnana, Yadana or Adana which was mentioned in an Assyrian tablet of the 8th century BC, as an island in the vicinity of Cyprus. Archaeological evidence exists that shows Dana Island had played a significant role in seamanship activities in Levant starting from Neolithic times. A substantial part of the naval campaigns must have involved Dana Island which used be the biggest shipyard/naval base of the Eastern Mediterranean. A 3D model of the island has been made by using photogrammetry and computer graphics methods and simulations were executed to check the hypotheses related to the involvement of Dana Island in the major sea battles of antiquity, such as Sea Battle of Lade in 495 BC.
POSSIBILITIES OF PROCESSING ARCHIVAL PHOTOGRAMMETRIC IMAGES CAPTURED BY ROLLEI 6006 METRIC CAMERA USING CURRENT METHOD
Authors: Dlesk A. , Raeva P. , Vach K.
Published: May 2018

Abstract. Processing of analog photogrammetric negatives using current methods brings new challenges and possibilities, for example, creation of a 3D model from archival images which enables the comparison of historical state and current state of cultural heritage objects. The main purpose of this paper is to present possibilities of processing archival analog images captured by photogrammetric camera Rollei 6006 metric. In 1994, the Czech company EuroGV s.r.o. carried out photogrammetric measurements of former limestone quarry the Great America located in the Central Bohemian Region in the Czech Republic. All the negatives of photogrammetric images, complete documentation, coordinates of geodetically measured ground control points, calibration reports and external orientation of images calculated in the Combined Adjustment Program are preserved and were available for the current processing. Negatives of images were scanned and processed using structure from motion method (SfM). The result of the research is a statement of what accuracy is possible to expect from the proposed methodology using Rollei metric images originally obtained for terrestrial intersection photogrammetry while adhering to the proposed methodology.
THE WINCKELMANN300 PROJECT: DISSEMINATION OF CULTURE WITH VIRTUAL REALITY AT THE CAPITOLINE MUSEUM IN ROME
Authors: Gonizzi Barsanti S. , Malatesta S. G. , Lella F. , Fanini B. , Sala F. , Dodero E. , Petacco L.
Published: May 2018

Abstract. The best way to disseminate culture is, nowadays, the creation of scenarios with virtual and augmented reality that supply the visitors of museums with a powerful, interactive tool that allows to learn sometimes difficult concepts in an easy, entertaining way. 3D models derived from reality-based techniques are nowadays used to preserve, document and restore historical artefacts. These digital contents are also powerful instrument to interactively communicate their significance to non-specialist, making easier to understand concepts sometimes complicated or not clear. Virtual and Augmented Reality are surely a valid tool to interact with 3D models and a fundamental help in making culture more accessible to the wide public. These technologies can help the museum curators to adapt the cultural proposal and the information about the artefacts based on the different type of visitor’s categories. These technologies allow visitors to travel through space and time and have a great educative function permitting to explain in an easy and attractive way information and concepts that could prove to be complicated. The aim of this paper is to create a virtual scenario and an augmented reality app to recreate specific spaces in the Capitoline Museum in Rome as they were during Winckelmann’s time, placing specific statues in their original position in the 18th century.
VARIABILITY OF REMOTE SENSING SPECTRAL INDICES IN BOREAL LAKE BASINS
Authors: Hakala T. , Pölönen I. , Honkavaara E. , Näsi R. , Hakala T. , Lindfors A.
Published: May 2018

Abstract. Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the parameters is more complicated. In this work some ideas are presented concerning the study of this dependence. The data used in this study were collected from the lake Hiidenvesi in southern Finland. The hyperspectral data consists of reflectances in 36 bands in the wavelength area 508…878 nm and the separately measured water quality parameters are turbidity, blue-green algae, chlorophyll, pH and dissolved oxygen. Hyperspectral data was used as bare band reflectances, but also in the form of two simple spectral indices: ratio A / B and difference A − B, where A and B go through all the bands. The correlations of the indices with the parameters were presented visually as 1- or 2-dimensional arrays. To examine the significance on the results of different variables, the data was classified in two different ways: the natural basins and the values of the water quality parameters. It was noticed that the variability of the correlation arrays was particularly strong among different basins in both the magnitude of correlation and the best performing indices. Further studies are needed to clarify which features of the basins are of most importance in predicting the shapes of the correlation arrays.
METRIC SCALE CALCULATION FOR VISUAL MAPPING ALGORITHMS
Authors: Hanel A. , Mitschke A. , Boerner R. , Van Opdenbosch D. , Hoegner L. , Brodie D. , Stilla U.
Published: May 2018

Abstract. Visual SLAM algorithms allow localizing the camera by mapping its environment by a point cloud based on visual cues. To obtain the camera locations in a metric coordinate system, the metric scale of the point cloud has to be known. This contribution describes a method to calculate the metric scale for a point cloud of an indoor environment, like a parking garage, by fusing multiple individual scale values. The individual scale values are calculated from structures and objects with a-priori known metric extension, which can be identified in the unscaled point cloud. Extensions of building structures, like the driving lane or the room height, are derived from density peaks in the point distribution. The extension of objects, like traffic signs with a known metric size, are derived using projections of their detections in images onto the point cloud. The method is tested with synthetic image sequences of a drive with a front-looking mono camera through a virtual 3D model of a parking garage. It has been shown, that each individual scale value improves either the robustness of the fused scale value or reduces its error. The error of the fused scale is comparable to other recent works.
PROTOTYPIC DEVELOPMENT AND EVALUATION OF A MEDIUM FORMAT METRIC CAMERA
Authors: Hastedt H. , Rofallski R. , Luhmann T. , Rosenbauer R. , Ochsner D. , Rieke-Zapp D.
Published: May 2018

Abstract. Engineering applications require high-precision 3D measurement techniques for object sizes that vary between small volumes (2–3 m in each direction) and large volumes (around 20 x 20 x 1–10 m). The requested precision in object space (1σ RMS) is defined to be within 0.1–0.2 mm for large volumes and less than 0.01 mm for small volumes. In particular, focussing large volume applications the availability of a metric camera would have different advantages for several reasons: 1) high-quality optical components and stabilisations allow for a stable interior geometry of the camera itself, 2) a stable geometry leads to a stable interior orientation that enables for an a priori camera calibration, 3) a higher resulting precision can be expected. With this article the development and accuracy evaluation of a new metric camera, the ALPA 12 FPS add|metric will be presented. Its general accuracy potential is tested against calibrated lengths in a small volume test environment based on the German Guideline VDI/VDE 2634.1 (2002). Maximum length measurement errors of less than 0.025 mm are achieved with different scenarios having been tested. The accuracy potential for large volumes is estimated within a feasibility study on the application of photogrammetric measurements for the deformation estimation on a large wooden shipwreck in the German Maritime Museum. An accuracy of 0.2 mm–0.4 mm is reached for a length of 28 m (given by a distance from a lasertracker network measurement). All analyses have proven high stabilities of the interior orientation of the camera and indicate the applicability for a priori camera calibration for subsequent 3D measurements.
CLASSIFICATION OF STRAWBERRY FRUIT SHAPE BY MACHINE LEARNING
Authors: Ishikawa T. , Hayashi A. , Nagamatsu S. , Kyutoku Y. , Dan I. , Wada T. , Oku K. , Saeki Y. , Uto T. , Tanabata T. , Isobe S. , Kochi N.
Published: May 2018

Abstract. Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.
INCORRECT MATCH DETECTION METHOD FOR ARCTIC SEA-ICE RECONSTRUCTION USING UAV IMAGES
Authors: Kim J.-I. , Kim H.-C.
Published: May 2018

Abstract. Shapes and surface roughness, which are considered as key indicators in understanding Arctic sea-ice, can be measured from the digital surface model (DSM) of the target area. Unmanned aerial vehicle (UAV) flying at low altitudes enables theoretically accurate DSM generation. However, the characteristics of sea-ice with textureless surface and incessant motion make image matching difficult for DSM generation. In this paper, we propose a method for effectively detecting incorrect matches before correcting a sea-ice DSM derived from UAV images. The proposed method variably adjusts the size of search window to analyze the matching results of DSM generated and distinguishes incorrect matches. Experimental results showed that the sea-ice DSM produced large errors along the textureless surfaces, and that the incorrect matches could be effectively detected by the proposed method.
DEEP LEARNING FOR LOWTEXTURED IMAGE MATCHING
Authors: Kniaz V. V. , Fedorenko V. V. , Fomin N. A.
Published: May 2018

Abstract. Low-textured objects pose challenges for an automatic 3D model reconstruction. Such objects are common in archeological applications of photogrammetry. Most of the common feature point descriptors fail to match local patches in featureless regions of an object. Hence, automatic documentation of the archeological process using Structure from Motion (SfM) methods is challenging. Nevertheless, such documentation is possible with the aid of a human operator. Deep learning-based descriptors have outperformed most of common feature point descriptors recently. This paper is focused on the development of a new Wide Image Zone Adaptive Robust feature Descriptor (WIZARD) based on the deep learning. We use a convolutional auto-encoder to compress discriminative features of a local path into a descriptor code. We build a codebook to perform point matching on multiple images. The matching is performed using the nearest neighbor search and a modified voting algorithm. We present a new “Multi-view Amphora” (Amphora) dataset for evaluation of point matching algorithms. The dataset includes images of an Ancient Greek vase found at Taman Peninsula in Southern Russia. The dataset provides color images, a ground truth 3D model, and a ground truth optical flow. We evaluated the WIZARD descriptor on the “Amphora” dataset to show that it outperforms the SIFT and SURF descriptors on the complex patch pairs.
VERSATILE MOBILE AND STATIONARY LOW-COST APPROACHES FOR HYDROLOGICAL MEASUREMENTS
Authors: Kröhnert M. , Eltner A.
Published: May 2018

Abstract. In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability. Today’s smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres.
EVALUATION OF GMSH MESHING ALGORITHMS IN PREPARATION OF HIGH-RESOLUTION WIND SPEED SIMULATIONS IN URBAN AREAS
Authors: Langheinrich M.
Published: May 2018

Abstract. This paper aims to evaluate the applicability of automatically generated meshes produced within the gmsh meshing framework in preparation for high resolution wind speed and atmospheric pressure simulations for detailed urban environments. The process of creating a skeleton geometry for the meshing process based on level of detail (LOD) 2 CityGML data is described. Gmsh itself offers several approaches for the 2D and 3D meshing process respectively. The different algorithms are shortly introduced and preliminary rated in regard to the mesh quality that is to be expected, as they differ inversely in terms of robustness and resulting mesh element quality. A test area was chosen to simulate the turbulent flow of wind around an urban environment to evaluate the different mesh incarnations by means of a relative comparison of the residuals resulting from the finite-element computational fluid dynamics (CFD) calculations. The applied mesh cases are assessed regarding their convergence evolution as well as final residual values, showing that gmsh 2D and 3D algorithm combinations utilizing the Frontal meshing approach are the preferable choice for the kind of underlying geometry as used in the on hand experiments.
CHANGE DETECTION IN REMOTE SENSING IMAGES USING CONDITIONAL ADVERSARIAL NETWORKS
Authors: Lebedev M. A. , Vizilter Y. V. , Vygolov O. V. , Knyaz V. A. , Rubis A. Y.
Published: May 2018

Abstract. We present a method for change detection in images using Conditional Adversarial Network approach. The original network architecture based on pix2pix is proposed and evaluated for difference map creation. The paper address three types of experiments: change detection in synthetic images without objects relative shift, change detection in synthetic images with small relative shift of objects, and change detection in real season-varying remote sensing images.
OPEN SOURCE CLOUD-BASED TECHNOLOGIES FOR BIM
Authors: Logothetis S. , Karachaliou E. , Valari E. , Stylianidis E.
Published: May 2018

Abstract. This paper presents a Cloud-based open source system for storing and processing data from a 3D survey approach. More specifically, we provide an online service for viewing, storing and analysing BIM. Cloud technologies were used to develop a web interface as a BIM data centre, which can handle large BIM data using a server. The server can be accessed by many users through various electronic devices anytime and anywhere so they can view online 3D models using browsers. Nowadays, the Cloud computing is engaged progressively in facilitating BIM-based collaboration between the multiple stakeholders and disciplinary groups for complicated Architectural, Engineering and Construction (AEC) projects. Besides, the development of Open Source Software (OSS) has been rapidly growing and their use tends to be united. Although BIM and Cloud technologies are extensively known and used, there is a lack of integrated open source Cloud-based platforms able to support all stages of BIM processes. The present research aims to create an open source Cloud-based BIM system that is able to handle geospatial data. In this effort, only open source tools will be used; from the starting point of creating the 3D model with FreeCAD to its online presentation through BIMserver. Python plug-ins will be developed to link the two software which will be distributed and freely available to a large community of professional for their use. The research work will be completed by benchmarking four Cloud-based BIM systems: Autodesk BIM 360, BIMserver, Graphisoft BIMcloud and Onuma System, which present remarkable results.
INVESTIGATIONS ON THE BUNDLE ADJUSTMENT RESULTS FROM SFM-BASED SOFTWARE FOR MAPPING PURPOSES
Authors: Lumban-Gaol Y. A. , Murtiyoso A. , Nugroho B. H.
Published: May 2018

Abstract. Since its first inception, aerial photography has been used for topographic mapping. Large-scale aerial photography contributed to the creation of many of the topographic maps around the world. In Indonesia, a 2013 government directive on spatial management has re-stressed the need for topographic maps, with aerial photogrammetry providing the main method of acquisition. However, the large need to generate such maps is often limited by budgetary reasons. Today, SfM (Structure-from-Motion) offers quicker and less expensive solutions to this problem. However, considering the required precision for topographic missions, these solutions need to be assessed to see if they provide enough level of accuracy. In this paper, a popular SfM-based software Agisoft PhotoScan is used to perform bundle adjustment on a set of large-scale aerial images. The aim of the paper is to compare its bundle adjustment results with those generated by more classical photogrammetric software, namely Trimble Inpho and ERDAS IMAGINE. Furthermore, in order to provide more bundle adjustment statistics to be compared, the Damped Bundle Adjustment Toolbox (DBAT) was also used to reprocess the PhotoScan project. Results show that PhotoScan results are less stable than those generated by the two photogrammetric software programmes. This translates to lower accuracy, which may impact the final photogrammetric product.
RESEARCH ON THE DIGITAL SIMULATION FOR THE WHOLE PROCESS OF MARS EXPLORATION
Authors: Lyu L. , Xu Q. , Zhou Y. , Xing S. , Lu W. , Zhao Y.
Published: May 2018

Abstract. China has paid considerable attention to space exploration and made great strides in the field. The first Chinese Mars Exploration Mission will be carried out in 2020. Digital simulation has been proved to be an effective and efficient means for planning and deduction in many fields. Thus, it was introduced for the Mars exploration in this paper and key technologies was researched above three aspects. First of all, complicated time-space benchmark was combed to support the interplanetary simulation. Secondly, the multi-resolution pyramid model and indexing strategy were adopted to preprocess the geographical environment data, which ensured the efficiency of data loading, browsing, and querying. Then, the activity objects were abstracted and modelled based on four aspects, including property, ephemeris, geometry, and behavior. Therefore, a digital simulation system, called Sino-Mars, was developed. The architecture of Sino- Mars consists of five layers, including data collection, data processing, scenario modelling, visualization and application layer. Using the Chinese Mars Exploration Mission slated for 2020 as an example, we demonstrated the capabilities of Sino-Mars for data integration, visualization, process deduction, and auxiliary analysis.
THE MULTITEMPORAL PHOTOGRAMMETRIC DATA IN ARCHAEOLOGICAL AND ARCHITECTURAL RESEARCH IN THE ROYAL CASTLE IN WARSAW – FIRST RESULTS
Authors: Markiewicz J. , Zawieska D. , Bocheńska A. , Tobiasz A. , Łapiński S.
Published: May 2018

Abstract. Modern measurement technologies are commonly applied not only to monitor Cultural Heritage objects; they are also applied during archaeological excavation works, when it is important to quickly perform measurements. The paper presents multitemporal integration of different image-based (UAV, close-range digital images) and range-based technologies (Terrestrial Laser Scanning), as well as data acquired in different periods, during archaeological works performed at the Royal Castle in Warsaw, especially for the Justice Court Tower. Measurements were performed in several periods, during deep archaeological excavation works. Due to the limited access to excavations different measurement technologies were applied which allowed to perform measurements within short time. As a results, the DSM (Digital Surface Model). the point cloud and orthoimages were generated. All of the products were stored in the GIS system which will be used for the needs of archaeological and architectural analyses.
MULTITEMPORAL ANALYSIS OF OBJECTS IN 3D POINT CLOUDS FOR LANDSLIDE MONITORING
Authors: Mayr A. , Rutzinger M. , Geitner C.
Published: May 2018

Abstract. To date multi-temporal 3D point clouds from close-range sensing are used for landslide and erosion monitoring in an operational manner. Morphological changes are typically derived by calculating distances between points from different acquisition epochs. The identification of the underlying processes resulting in surface changes, however, is often challenging, for example due to the complex surface structures and influences from seasonal vegetation dynamics. We present an approach for object-based 3D landslide monitoring based on topographic LiDAR point cloud time series separating specific surface change types automatically. The workflow removes vegetation and relates surface changes derived from a point cloud time series directly to (i) geomorphological object classes (landslide scarp, eroded area, deposit) and (ii) to individual, spatially contiguous objects (such as parts of the landslide scarp and clods of material moving in the landslide). We apply this approach to a time series of nine point cloud epochs from a slope affected by two shallow landslides. A parameter test addresses the influence of the registration error and the associated level of detection on the magnitude of derived object changes. The results of our case study are in accordance with field observations at the test site as well as conceptual landslide models, where retrogressive erosion of the scarp and downslope movement of the sliding mass are major principles of secondary landslide development. We conclude that the presented methods are well suited to extract information on geomorphological process dynamics from the complex point clouds and aggregate it at different levels of abstraction to assist landslide and erosion assessment.
IMPROVING UNDERWATER ACCURACY BY EMPIRICAL WEIGHTING OF IMAGE OBSERVATIONS
Authors: Menna F. , Nocerino E. , Drap P. , Remondino F. , Murtiyoso A. , Grussenmeyer P. , Börlin N.
Published: May 2018

Abstract. An underwater imaging system with camera and lens behind a flat port does not behave as a standard pinhole camera with additional parameters. Indeed, whenever the entrance pupil of the lens is not in contact with the flat port, the standard photogrammetric model is not suited anymore and an extended mathematical model that considers the different media would be required. Therefore, when dealing with flat ports, the use of the classic photogrammetric formulation represents a simplification of the image formation phenomenon, clearly causing a degradation in accuracy. Furthermore, flat ports significantly change the characteristics of the enclosed imaging device and negatively affect the image quality, introducing heavy curvilinear distortions and optical aberrations. With the aim of mitigating the effect of systematic errors introduced by a combination of (i) image quality degradation, induced by the flat ports, and (ii) a non-rigorous modelling of refraction, this paper presents a stochastic model for image observations that penalises those that are more affected by aberrations and departure from the pinhole model. Experiments were carried out at sea and in pools showing that the use of the proposed stochastic model is beneficial for the final accuracy with improvements up to 50 %.
ETALON IMAGES: UNDERSTANDING THE CONVOLUTION NEURAL NETWORKS
Authors: Molchanov V. V. , Vishnyakov B. V. , Gorbatsevich V. S. , Vizilter Y. V.
Published: May 2018

Abstract. In this paper we propose a new technic called etalons, which allows us to interpret the way how convolution network makes its predictions. This mechanism is very similar to voting among different experts. Thereby CNN could be interpreted as a variety of experts, but it acts not like a sum or product of them, but rather represent a complicated hierarchy. We implement algorithm for etalon acquisition based on well-known properties of affine maps. We show that neural net has two high-level mechanisms of voting: first, based on attention to input image regions, specific to current input, and second, based on ignoring specific input regions. We also make an assumption that there is a connection between complexity of the underlying data manifold and the number of etalon images and their quality.