scholarly journals UAV oblique photogrammetry and lidar data acquisition for 3D documentation of the Hercules Fountain

2017 ◽  
Vol 8 (16) ◽  
pp. 83 ◽  
Author(s):  
Filiberto Chiabrando ◽  
Antonia Spanò ◽  
Giulia Sammartano ◽  
Lorenzo Teppati Losè
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
Large Scale ◽  
Continuous Model ◽  
Complex Objects ◽  
Cost Cutting ◽  
3D Data ◽  
Close Range ◽  
Precision Time ◽  
3D Documentation

This paper discusses some enhancements concerning 3D modelling, and the integration and comparison of 3D data from aerial and terrestrial sensors, developed by innovative geomatics techniques around the metric documentation of cultural heritage. In archaeology, it is interesting to deal with the considerable advantages of new multi-sensor approaches for the data acquisition and the management phases in terms of the sustainability (automated acquisition, quickness, precision, time and cost cutting). In particular, Unmanned Aerial Vehicles(UAVs)photogrammetry with the joint use of nadir and oblique cameras can be usefully combined with the large-scale details acquired by the terrestrial Light Detection and Ranging (LiDAR)in vast areas or complex objects, especially in mostly vertical sized objects. Here, we will report the results of an integrated 3D survey in an archaeological context in the Piedmont region of Italy. The Hercules Fountain is located in the gardens of the Venaria Reale (a Savoy Royal Palace included in the UNESCO heritage list) and has witnessed several events and historical phases during the past centuries–from its construction in the 16thcentury to its disuse and decline in the 17thcentury, right up to the 21stcentury when it was eventually brought back to light. The goal of the test is the creation of a3D continuous model of the site for documentation purposes, future consolidation, and enhancement projects finalised fora public promotion. To meet these strategic aims, a terrestrial laser scanning (TLS henceforth) survey has been designed together with multi-flights by a multi-rotor UAV and terrestrial close-range photogrammetry (CRP) acquisition to produce a highly detailed 3D textured model from which we have inferred standard 2D drawings, digital orthoimages, and further 3D products. In conclusion, the entire workflow and the outputs have been compared together to evaluate the effectiveness of each elaboration according to the different goals of the survey.

The Application of 3D Laser Scanning Technology in Ancient Architecture Protection

2013 ◽  
Vol 353-356 ◽  
pp. 3476-3479
Author(s):  
Jun Lan Zhao ◽  
Ran Wu ◽  
Lei Wang ◽  
Yi Qin Wu
Keyword(s):  
3D Reconstruction ◽  
Data Acquisition ◽  
High Speed ◽  
Laser Scanning ◽  
Large Scale ◽  
High Efficiency ◽  
Image Data ◽  
High Accuracy ◽  
3D Laser Scanning ◽  
3D Data

The study of 3D laser scanning technology in Category Conservation is one of the hot researches in recent years. Through the high-speed laser scanning, catching the 3D data of an object in large-scale with high efficiency, high accuracy and excellent resolution, is a new way in 3D reconstruction and image data acquisition. The method has achieved good results through the experiment.

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.

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 3D MODELS OF THE QH31, QH32 AND QH33 TOMBS IN QUBBET EL HAWA (ASWAN, EGYPT)

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 1427-1434
Author(s):  
A. T. Mozas-Calvache ◽  
J. L. Pérez-García ◽  
J. M. Gómez-López ◽  
J. L. Martínez de Dios ◽  
A. Jiménez-Serrano
Keyword(s):  
Laser Scanning ◽  
3D Model ◽  
Terrestrial Laser Scanning ◽  
3D Models ◽  
Complex Geometries ◽  
Spatial Behaviour ◽  
Reduced Dimensions ◽  
Adjacent Structures ◽  
Close Range ◽  
3D Documentation

Abstract. This paper describes the methodology employed to obtain 3D models of three funerary complexes (QH31, QH32 and QH33) of the Necropolis of Qubbet el Hawa (Aswan, Egypt) and the main results obtained. These rock-cut tombs are adjacent structures defined by complex geometries such as chambers, corridors and vertical shafts. The main goal of this study was to discover the spatial relationships between them and obtain a complete 3D model. In addition, some models with realistic textures of the burial chambers were demanded in order to analyse archaeological, architectural and geological aspects. The methodology was based on the use of Terrestrial Laser Scanning and Close Range Photogrammetry. In general, both techniques were developed in parallel for each tomb. Some elements presented difficulties because of their reduced dimensions, the presence of vertical falls, some objects stored in the tombs that generated occlusions of some walls, coincidence of other workers, poor illumination conditions, etc. The results included three complete 3D models obtained without texture and some parts of interest obtained with real textures. All models were merged into a global 3D model. The information extracted from this product has helped architects and archaeologists to contrast their premises about the spatial behaviour of the tombs. The results have also allowed the obtaining of the first 3D documentation of these tombs under the same reference system, allowing them to be studied completely. This information is very important for documentation purposes but also to understand the spatial behaviour of these structures and the excavation processes developed by ancient Egyptians 4000 years ago.

scholarly journals CLOSE RANGE UAV ACCURATE RECORDING AND MODELING OF ST-PIERRE-LE-JEUNE NEO-ROMANESQUE CHURCH IN STRASBOURG (FRANCE)

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 519-526 ◽  
Author(s):  
A. Murtiyoso ◽  
P. Grussenmeyer ◽  
T. Freville
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Geographical Information ◽  
Close Range Photogrammetry ◽  
Dense Matching ◽  
Dense Point ◽  
Close Range ◽  
Calibration Accuracy ◽  
3D Documentation

Close-range photogrammetry is an image-based technique which has often been used for the 3D documentation of heritage objects. Recently, advances in the field of image processing and UAVs (Unmanned Aerial Vehicles) have resulted in a renewed interest in this technique. However, commercially ready-to-use UAVs are often equipped with smaller sensors in order to minimize payload and the quality of the documentation is still an issue. In this research, two commercial UAVs (the Sensefly Albris and DJI Phantom 3 Professional) were setup to record the 19<sup>th</sup> century St-Pierre-le-Jeune church in Strasbourg, France. Several software solutions (commercial and open source) were used to compare both UAVs’ images in terms of calibration, accuracy of external orientation, as well as dense matching. Results show some instability in regards to the calibration of Phantom 3, while the Albris had issues regarding its aerotriangulation results. Despite these shortcomings, both UAVs succeeded in producing dense point clouds of up to a few centimeters in accuracy, which is largely sufficient for the purposes of a city 3D GIS (Geographical Information System). The acquisition of close range images using UAVs also provides greater LoD flexibility in processing. These advantages over other methods such as the TLS (Terrestrial Laser Scanning) or terrestrial close range photogrammetry can be exploited in order for these techniques to complement each other.

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.

Close-range sensing and object-based analysis of shallow landslides and erosion in grasslands

2020 ◽  
Author(s):  
Andreas Mayr ◽  
Martin Rutzinger ◽  
Magnus Bremer ◽  
Clemens Geitner
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Case Studies ◽  
Laser Scanning ◽  
Regional Scale ◽  
Shallow Landslides ◽  
Range Sensing ◽  
Erosion Processes ◽  
Object Based ◽  
Close Range

&lt;p&gt;Close-range sensing methods for topographic data acquisition, such as Structure-from-Motion with multi-view stereo (SfM-MVS) photogrammetry and laser scanning from the ground or from unmanned aerial systems (UAS), have strongly improved over the last decade. As they are providing data with sub-decimetre resolution and accuracy, these methods open new possibilities for bridging the gap between local in-situ observations and area-wide space-borne or aerial remote sensing. For assessments of shallow landslides and erosion patches, which are wide-spread phenomena in mountain grasslands, the potential of close-range sensing is two-fold: Firstly, it could provide accurate reference data for assessing the geometric accuracy of a catchment or regional scale eroded area monitoring based on aerial or satellite remote sensing systems. Secondly, selected sites can be monitored at a very detailed local scale to reveal processes of secondary erosion or natural vegetation succession and slope stabilisation. Furthermore, high-resolution 4D data from multi-temporal close-range sensing make it possible to quantify volumes and rates of displacement at erosion features. In this contribution, we propose to exploit this potential of close-range sensing for landslide and erosion studies with object-based approaches for raster and 3D point cloud analyses. Assuming that erosion features can be discriminated from undisturbed grassland and from trees and shrubs, based on their morphometric and spectral signatures, we show how computer vision and machine learning techniques help to detect and label these features automatically as spatial objects in the data. We combine this object detection and labelling with 2.5D differential elevation models and with 3D deformation analysis of point clouds. This strategy addresses one of the key challenges of automatically analysing close-range sensing data in geomorphological studies, i.e. linking geometric information (such as the size and shape of erosion features or the surface change across a time series) with semantic information (e.g. separating vegetation from complex ground structures). In three case studies from recent projects in the Alps, where we acquired data by UAS, terrestrial laser scanning and terrestrial photogrammetry, we demonstrate the use of these new methodological developments. The methods tested can reliably detect changes with minimum magnitudes of centimetre to decimetre level, depending primarily on the specific data acquisition setup. By automatically relating these changes to erosion features of different scales (i.e. both at entire eroded areas and at their components, e.g. collapsing parts of the scarp), such analyses can provide valuable insights regarding process dynamics. In our tests, close-range sensing and automated data analysis workflows helped to understand both the development of new eroded areas as well as their enlargement by secondary erosion processes or episodic landslide reactivation. Based on the experience from these case studies, we also discuss the main challenges and limitations of these methods for erosion monitoring applications.&lt;/p&gt;

scholarly journals SUBMANIFOLD SPARSE CONVOLUTIONAL NETWORKS FOR SEMANTIC SEGMENTATION OF LARGE-SCALE ALS POINT CLOUDS

2019 ◽  
Vol IV-2/W5 ◽  
pp. 77-84 ◽  
Author(s):  
S. Schmohl ◽  
U. Sörgel
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Computing Time ◽  
Semantic Segmentation ◽  
Point Clouds ◽  
Convolutional Networks ◽  
Airborne Laser ◽  
Semantic Labeling ◽  
3D Data ◽  
Automated Processing

<p><strong>Abstract.</strong> Semantic segmentation of point clouds is one of the main steps in automated processing of data from Airborne Laser Scanning (ALS). Established methods usually require expensive calculation of handcrafted, point-wise features. In contrast, Convolutional Neural Networks (CNNs) have been established as powerful classifiers, which at the same time also learn a set of features by themselves. However, their application to ALS data is not trivial. Pure 3D CNNs require a lot of memory and computing time, therefore most related approaches project ALS point clouds into two-dimensional images. Sparse Submanifold Convolutional Networks (SSCNs) address this issue by exploiting the sparsity often inherent in 3D data. In this work, we propose the application of SSCNs for efficient semantic segmentation of voxelized ALS point clouds in an end-to-end encoder-decoder architecture. We evaluate this method on the ISPRS Vaihingen 3D Semantic Labeling benchmark and achieve state-of-the-art 85.0% overall accuracy. Furthermore, we demonstrate its capabilities regarding large-scale ALS data by classifying a 2.5&amp;thinsp;km<sup>2</sup> subset containing 41&amp;thinsp;M points from the Actueel Hoogtebestand Nederland (AHN3) with 95% overall accuracy in just 48&amp;thinsp;s inference time or with 96% in 108&amp;thinsp;s.</p>

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