3D City Modeling and Visualization for Smart Phone Applications

2012 ◽  
pp. 254-296
Author(s):  
Juha Hyyppä ◽  
Lingli Zhu ◽  
Zhengjun Liu ◽  
Harri Kaartinen ◽  
Anttoni Jaakkola
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
3D Models ◽  
Image Capture ◽  
3D City Models ◽  
Central Computer ◽  
3D Data ◽  
Open Operation ◽  
City Modeling ◽  
City Models

Smartphones with larger screens, powerful processors, abundant memory, and an open operation system provide many possibilities for 3D city or photorealistic model applications. 3D city or photorealistic models can be used by the users to locate themselves in the 3D world, or they can be used as methods for visualizing the surrounding environment once a smartphone has already located the phone by other means, e.g. by using GNSS, and then to provide an interface in the form of a 3D model for the location-based services. In principle, 3D models can be also used for positioning purposes. For example, matching of images exported from the smartphone and then registering them in the existing 3D photorealistic world provides the position of the image capture. In that process, the central computer can do a similar image matching task when the users locate themselves interactively into the 3D world. As the benefits of 3D city models are obvious, this chapter demonstrates the technology used to provide photorealistic 3D city models and focus on 3D data acquisition and the methods available in 3D city modeling, and the development of 3D display technology for smartphone applications. Currently, global geoinformatic data providers, such as Google, Nokia (NAVTEQ), and TomTom (Tele Atlas), are expanding their products from 2D to 3D. This chapter is a presentation of a case study of 3D data acquisition, modeling and mapping, and visualization for a smartphone, including an example based on data collected by mobile laser scanning data from the Tapiola (Espoo, Finland) test field.

3D City Modeling and Visualization for Smart Phone Applications

2013 ◽  
pp. 1011-1052 ◽  
Author(s):  
Juha Hyyppä ◽  
Lingli Zhu ◽  
Zhengjun Liu ◽  
Harri Kaartinen ◽  
Anttoni Jaakkola
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
3D Models ◽  
Image Capture ◽  
3D City Models ◽  
Central Computer ◽  
3D Data ◽  
Open Operation ◽  
City Modeling ◽  
City Models

Smartphones with larger screens, powerful processors, abundant memory, and an open operation system provide many possibilities for 3D city or photorealistic model applications. 3D city or photorealistic models can be used by the users to locate themselves in the 3D world, or they can be used as methods for visualizing the surrounding environment once a smartphone has already located the phone by other means, e.g. by using GNSS, and then to provide an interface in the form of a 3D model for the location-based services. In principle, 3D models can be also used for positioning purposes. For example, matching of images exported from the smartphone and then registering them in the existing 3D photorealistic world provides the position of the image capture. In that process, the central computer can do a similar image matching task when the users locate themselves interactively into the 3D world. As the benefits of 3D city models are obvious, this chapter demonstrates the technology used to provide photorealistic 3D city models and focus on 3D data acquisition and the methods available in 3D city modeling, and the development of 3D display technology for smartphone applications. Currently, global geoinformatic data providers, such as Google, Nokia (NAVTEQ), and TomTom (Tele Atlas), are expanding their products from 2D to 3D. This chapter is a presentation of a case study of 3D data acquisition, modeling and mapping, and visualization for a smartphone, including an example based on data collected by mobile laser scanning data from the Tapiola (Espoo, Finland) test field.

scholarly journals Photogrammetry: What, How, and Where

10.5334/bck.d ◽  
2021 ◽  
pp. 25-37
Author(s):  
Hafizur Rahaman
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
3D Models ◽  
Heritage Management ◽  
Quality Data ◽  
Digital Platforms ◽  
3D Data ◽  
Virtual Visits ◽  
Digital Documentation ◽  
3D Digital Models

Developing 3D digital models of artefacts, monuments, excavations and historic landscapes as part of digital documentation is becoming common in the field of heritage management, virtual tourism, immersive Due to the present pandemic situation with restricted social distancing; gallery, library, archive, and museum (GLAM) industries are facing an incremental burden on both their income and visitor traffic, which is affecting their survival. As a way out, we can see some GLAM institutes are trying to expand their collections on digital platforms for showcasing and promoting virtual visits. Numerous online portals and repositories are evolving for archiving, sharing, and trading 3D models are also evolving to support this digital vibe. This chapter explains the basics of photogrammetry and its development workflow, including data acquisition (photo shooting), data processing and a few post-processing tools. visualisation and scientific research. Such 3D reconstruction or 3D data acquisition form a laser scanning process involves high costs, manual labour and substantial expertise. On the other hand, Image-based 3D modelling photogrammetry software offers a comparatively inexpensive alternative and can handle the task with ease. Besides, documenting heritage artefacts with free and open-source software (FOSS) in supporting photogrammetry is getting popular for quality data production.

scholarly journals INTEGRATION OF DATA OBTAINED BY PHOTOGRAMMETRIC METHODS SUCH AS A TERRESTRIAL LASER SCANNER AND UAV SYSTEM AND USE IN 3D CITY MODELS: THE CASE OF KÖYCEĞİZ CAMPUS

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 187-192
Author(s):  
İ. Dursun ◽  
A. Varlık
Keyword(s):  
Information And Communication Technologies ◽  
Laser Scanning ◽  
Smart Cities ◽  
Complex Structure ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Models ◽  
3D City Models ◽  
Social Sciences And Humanities ◽  
City Models

Abstract. The ever-growing and complex structure of cities has increased the need to include advanced information and communication technologies in management processes. In parallel with this, the concept of smart cities has emerged and the creation and use of three-dimensional (3D) city models have become one of the most important components for tracking cities online. Depending on technological advances; Photogrammetric methods come to the fore in surveying because it offers convenience in terms of cost and time. Among the photogrammetric methods, mobile laser scanning and UAV (Unmanned Aerial Vehicle) systems have become very popular. In this study; Necmettin Erbakan University, Faculty of Social Sciences and Humanities (SBIF), located in Köyceğiz Campus, was chosen as the study area and focused on integrating three-dimensional (3D) models produced by terrestrial and aerial photogrammetry under the theme of smart cities.

scholarly journals ENHANCEMENT OF GENERIC BUILDING MODELS BY RECOGNITION AND ENFORCEMENT OF GEOMETRIC CONSTRAINTS

2016 ◽  
Vol III-3 ◽  
pp. 333-338 ◽  
Author(s):  
J. Meidow ◽  
H. Hammer ◽  
M. Pohl ◽  
D. Bulatov
Keyword(s):  
Laser Scanning ◽  
Initial Point ◽  
Real Data ◽  
Boundary Representation ◽  
Geometric Constraints ◽  
Data Set ◽  
3D City Models ◽  
Building Models ◽  
Recognition And Enforcement ◽  
City Models

Many buildings in 3D city models can be represented by generic models, e.g. boundary representations or polyhedrons, without expressing building-specific knowledge explicitly. Without additional constraints, the bounding faces of these building reconstructions do not feature expected structures such as orthogonality or parallelism. The recognition and enforcement of man-made structures within model instances is one way to enhance 3D city models. Since the reconstructions are derived from uncertain and imprecise data, crisp relations such as orthogonality or parallelism are rarely satisfied exactly. Furthermore, the uncertainty of geometric entities is usually not specified in 3D city models. Therefore, we propose a point sampling which simulates the initial point cloud acquisition by airborne laser scanning and provides estimates for the uncertainties. We present a complete workflow for recognition and enforcement of man-made structures in a given boundary representation. The recognition is performed by hypothesis testing and the enforcement of the detected constraints by a global adjustment of all bounding faces. Since the adjustment changes not only the geometry but also the topology of faces, we obtain improved building models which feature regular structures and a potentially reduced complexity. The feasibility and the usability of the approach are demonstrated with a real data set.

scholarly journals INVESTIGATING INTEROPERABILITY CAPABILITIES BETWEEN IFC AND CITYGML LOD 4 – RETAINING SEMANTIC INFORMATION

2018 ◽  
Vol XLII-4/W10 ◽  
pp. 33-40 ◽  
Author(s):  
G. S. Floros ◽  
C. Ellul ◽  
E. Dimopoulou
Keyword(s):  
Semantic Information ◽  
Open Data ◽  
3D Models ◽  
Solar Panels ◽  
3D City Models ◽  
Information Models ◽  
Building Information ◽  
Consistent Manner ◽  
3D Information ◽  
City Models

<p><strong>Abstract.</strong> Applications of 3D City Models range from assessing the potential output of solar panels across a city to determining the best location for 5G mobile phone masts. While in the past these models were not readily available, the rapid increase of available data from sources such as Open Data (e.g. OpenStreetMap), National Mapping and Cadastral Agencies and increasingly Building Information Models facilitates the implementation of increasingly detailed 3D Models. However, these sources also generate integration challenges relating to heterogeneity, storage and efficient management and visualization. CityGML and IFC (Industry Foundation Classes) are two standards that serve different application domains (GIS and BIM) and are commonly used to store and share 3D information. The ability to convert data from IFC to CityGML in a consistent manner could generate 3D City Models able to represent an entire city, but that also include detailed geometric and semantic information regarding its elements. However, CityGML and IFC present major differences in their schemas, rendering interoperability a challenging task, particularly when details of a building’s internal structure are considered (Level of Detail 4 in CityGML). The aim of this paper is to investigate interoperability options between the aforementioned standards, by converting IFC models to CityGML LoD 4 Models. The CityGML Models are then semantically enriched and the proposed methodology is assessed in terms of model’s geometric validity and capability to preserve semantics.</p>

scholarly journals Applicability Assessments of Close-Range Photogrammetry for Slope Face 3D Modelling

2020 ◽  
Vol 8 (3) ◽  
pp. 143-150
Author(s):  
Haqul Baramsyah ◽  
Less Rich
Keyword(s):  
Laser Scanning ◽  
3D Model ◽  
Laser Scanner ◽  
Cost Effective ◽  
3D Models ◽  
Digital Photogrammetry ◽  
Aerial Photogrammetry ◽  
3D Data ◽  
Image Capturing ◽  
Close Range

The digital single lens reflex (DSLR) cameras have been widely accepted to use in slope face photogrammetry rather than the expensive metric camera used for aerial photogrammetry. 3D models generated from digital photogrammetry can approach those generated from terrestrial laser scanning in term of scale and level of detail. It is cost effective and has equipment portability. This paper presents and discusses the applicability of close-range digital photogrammetry to produce 3D models of rock slope faces. Five experiments of image capturing method were conducted to capture the photographs as the input data for processing. As a consideration, the appropriate baseline lengths to capture the slope face to get better result are around 1/6 to 1/8 of target distance.  A fine quality of 3D model from data processing is obtained using strip method and convergent method with 80% overlapping in each photograph. A random camera positions with different distances from the slope face can also generate a good 3D model, however the entire target should be captured in each photograph. The accuracy of the models is generated by comparing the 3D models produced from photogrammetry with the 3D data obtained from laser scanner. The accuracy of 3D models is quite satisfactory with the mean error range from 0.008 to 0.018 m.

scholarly journals PLASTIC SURGERY FOR 3D CITY MODELS: A PIPELINE FOR AUTOMATIC GEOMETRY REFINEMENT AND SEMANTIC ENRICHMENT

2021 ◽  
Vol V-4-2021 ◽  
pp. 17-24
Author(s):  
O. Wysocki ◽  
B. Schwab ◽  
L. Hoegner ◽  
T. H. Kolbe ◽  
U. Stilla
Keyword(s):  
Point Clouds ◽  
3D Models ◽  
Data Types ◽  
Automated Driving ◽  
3D City Models ◽  
Semantic Enrichment ◽  
Simulation Engine ◽  
Global Accuracy ◽  
Model Database ◽  
City Models

Abstract. Nowadays, the number of connected devices providing unstructured data is rapidly rising. These devices acquire data with a temporal and spatial resolution at an unprecedented level creating an influx of geoinformation which, however, lacks semantic information. Simultaneously, structured datasets like semantic 3D city models are widely available and assure rich semantics and high global accuracy but are represented by rather coarse geometries. While the mentioned downsides curb the usability of these data types for nowadays’ applications, the fusion of both shall maximize their potential. Since testing and developing automated driving functions stands at the forefront of the challenges, we propose a pipeline fusing structured (CityGML and HD Map datasets) and unstructured datasets (MLS point clouds) to maximize their advantages in the automatic 3D road space models reconstruction domain. The pipeline is a parameterized end-to-end solution that integrates segmentation, reconstruction, and modeling tasks while ensuring geometric and semantic validity of models. Firstly, the segmentation of point clouds is supported by the transfer of semantics from a structured to an unstructured dataset. The distinction between horizontal- and vertical-like point cloud subsets enforces a further segmentation or an immediate refinement while only adequately depicted models by point clouds are allowed. Then, based on the classified and filtered point clouds the input 3D model geometries are refined. Building upon the refinement, the semantic enrichment of the 3D models is presented. The deployment of a simulation engine for automated driving research and a city model database tool underlines the versatility of possible application areas.

3D-GIS for support of works on geotechnical monitoring of objects of main pipelines

2020 ◽  
Vol 10 (4) ◽  
pp. 342-351
Author(s):  
Elizaveta M. Makarycheva ◽  
◽  
Тaras I. Kuznetsov ◽  
Sergey A. Polovkov ◽  
Alexander I. Baryshev ◽  
...  
Keyword(s):  
Laser Scanning ◽  
3D Models ◽  
3D Gis ◽  
Distributed Information ◽  
Geotechnical Monitoring ◽  
3D Data ◽  
Main Pipelines ◽  
Research Problems ◽  
Automated Processing ◽  
Geographically Distributed

The article presents the results of the development of specialized 3D-GIS as a tool for structuring, storing, reproducing, processing and analyzing data for geotechnical monitoring of main pipeline facilities. The authors proposed a solution to the problem of the complexity of processing large amounts of data by creating a unified environment of geographically distributed information through a geo-portal and implementing services on the basis of the geo-portal for automated processing and analysis of information, as well as computational algorithms. The description of the structure and functionality of the developed 3D-GIS is given. Methods for obtaining and processing 3D data are disclosed, and the data is analyzed. Results of a quantitative assessment of changes in the natural environment, plan-elevation position and geometry of objects based on the data of several cycles of surveys by methods of ground and air laser scanning are presented. The advantages of 3D-GIS in solving problems of geotechnical monitoring, as well as the possibility of using 3D-models for solving other production and research problems are highlighted.

scholarly journals A Method for the Automated Construction of 3D Models of Cities and Neighborhoods from Official Cadaster Data for Solar Analysis

2021 ◽  
Vol 13 (11) ◽  
pp. 6028
Author(s):  
Carlos Beltran-Velamazan ◽  
Marta Monzón-Chavarrías ◽  
Belinda López-Mesa
Keyword(s):  
3D Model ◽  
3D Models ◽  
Automatic Method ◽  
Time Saving ◽  
Automatic Construction ◽  
3D City Models ◽  
Solar Analysis ◽  
Solar Access ◽  
Short Time ◽  
City Models

3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400,000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h.

scholarly journals TESTING THE IMPACT OF 2D GENERALISATION ON 3D MODELS – EXPLORING ANALYSIS OPTIONS WITH AN OFF-THE-SHELF SOFTWARE PACKAGE

2018 ◽  
Vol XLII-4/W10 ◽  
pp. 119-126
Author(s):  
E. Muñumer Herrero ◽  
C. Ellul ◽  
J. Morley
Keyword(s):  
3D Models ◽  
3D Analysis ◽  
Spatial Analyses ◽  
3D City Models ◽  
The Third ◽  
The Past ◽  
Processing Times ◽  
Third Dimension ◽  
The Impact ◽  
City Models

<p><strong>Abstract.</strong> Popularity and diverse use of 3D city models has increased exponentially in the past few years, providing a more realistic impression and understanding of cities. Often, 3D city models are created by elevating the buildings from a detailed 2D topographic base map and subsequently used in studies such as solar panel allocation, infrastructure remodelling, antenna installations or even tourist guide applications. However, the large amount of resulting data slows down rendering and visualisation of the 3D models, and can also impact the performance of any analysis. Generalisation enables a reduction in the amount of data – however the addition of the third dimension makes this process more complex, and the loss of detail resulting from the process will inevitably have an impact on the result of any subsequent analysis.</p><p>While a few 3D generalization algorithms do exist in a research context, these are not available commercially. However, GIS users can create the generalised 3D models by simplifying and aggregating the 2D dataset first and then extruding it to the third dimension. This approach offers a rapid generalization process to create a dataset to underpin the impact of using generalised data for analysis. Specifically, in this study, the line of sight from a tall building and the sun shadow that it creates are calculated and compared, in both original and generalised datasets. The results obtained after the generalisation process are significant: both the number of polygons and the number of nodes are minimized by around 83<span class="thinspace"></span>% and the volume of 3D buildings is reduced by 14.87<span class="thinspace"></span>%. As expected, the spatial analyses processing times are also reduced. The study demonstrates the impact of generalisation on analytical results – which is particularly relevant in situations where detailed data is not available and will help to guide the development of future 3D generalisation algorithms. It also highlights some issues with the overall maturity of 3D analysis tools, which could be one factor limiting uptake of 3D GIS.</p>

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