3D Acquisition and Preprocessing

2018 ◽  
pp. 41-63
Keyword(s):  
3D Acquisition

scholarly journals Metadata schema and ontology for capturing and processing of 3D cultural heritage objects

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Timo Homburg ◽  
Anja Cramer ◽  
Laura Raddatz ◽  
Hubert Mara
Keyword(s):  
Cultural Heritage ◽  
Measurement Data ◽  
Image Generation ◽  
3D Scanner ◽  
Fine Detail ◽  
3D Scanners ◽  
3D Acquisition ◽  
3D Processing ◽  
Cultural Heritage Objects ◽  
Processing Steps

AbstractMotivated by the increased use of 3D acquisition of objects by cultural heritage institutions, we were investigating ontologies and metadata schemes for the acquisition process to provide details about the 3D capturing, which can be combined with preexisting ontologies describing an object. Therefore we divided the 3D capturing workflow into common steps starting with the object being placed in front of a 3D scanner to preparation and publication of the 3D datasets and/or derived images. While the proposed ontology is well defined on a coarse level of detail for very different techniques, e.g. Stucture from Motion and LiDAR we elaborated the metadata scheme in very fine detail for 3D scanners available at our institutions. This includes practical experiments with measurement data from past and current projects including datasets published at Zenodo as guiding examples and the source code for their computation. Additionally, the free and Open Source GigaMesh Software Framework’s analysis and processing methods have been extended to provide metadata about the 3D processing steps like mesh cleaning as well as 2D image generation. Finally, we discuss the current limitations and give an outlook about future extensions.

P32.14: Quality control of standardized 3D acquisition for the examination of the fetal head and abdomen

2010 ◽  
Vol 36 (S1) ◽  
pp. 293-293
Author(s):  
P. Bouhanna ◽  
T. Quibel ◽  
S. Aimot ◽  
J. Bault ◽  
J. Bernard ◽  
...  
Keyword(s):  
Quality Control ◽  
Fetal Head ◽  
3D Acquisition

scholarly journals Segmentación de mallas 3d de edificios históricos para levantamiento arquitectónico

2018 ◽  
Vol 9 (18) ◽  
pp. 66
Author(s):  
Borja Javier Herráez ◽  
Eduardo Vendrell
Keyword(s):  
Feature Detection ◽  
3D Model ◽  
Three Dimensional ◽  
Recognition Algorithm ◽  
Mesh Segmentation ◽  
Historic Buildings ◽  
3D Mesh ◽  
Fields Of Study ◽  
Computer Based ◽  
3D Acquisition

<p>Advances in three-dimensional (3D) acquisition systems have introduced this technology to more fields of study, such as archaeology or architecture. In the architectural field, scanning a building is one of the first possible steps from which a 3D model can be obtained and can be later used for visualisation and/or feature analysis, thanks to computer-based pattern recognition tools. The automation of these tools allows for temporal savings and has become a strong aid for professionals, so that more and more methods are developed with this objective. In this article, a method for 3D mesh segmentation focused  on  the representation  of  historic  buildings  is  proposed.  This  type  of  buildings is characterised  by  having singularities  and features in  façades, such  as  doors  or  windows. The  main  objective  is  to  recognise  these  features, understanding them as those parts of the model that differ from the main structure of the building. The idea is to use a recognition algorithm for planar faces that allows users to create a graph showing the connectivity between them, therefore allowing the reflection of the shape of the 3Dmodel. At a later step, this graph is matched against some pre-defined graphs that  represent  the  patterns  to  look  for. Each  coincidence  between  both  graphs  indicate  the  position  of  one  of  the characteristics sought. The developed method has proved to be effective for feature detection and suitable for inclusion in architectural surveying applications.</p>

scholarly journals HIGH RESOLUTION 3D ACQUISITION AND MODELLING IN CULTURAL HERITAGE KNOWLEDGE AND RESTORATION PROJECTS: THE SURVEY OF THE FOUNTAIN OF NEPTUNE IN BOLOGNA

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 573-578 ◽  
Author(s):  
V. A. Girelli ◽  
M. A. Tini ◽  
M. Dellapasqua ◽  
G. Bitelli
Keyword(s):  
Information System ◽  
Laser Scanning ◽  
3D Model ◽  
Ad Hoc ◽  
Complex Object ◽  
Visual Computing ◽  
Precision Level ◽  
3D Acquisition ◽  
The University ◽  
User Friendly

<p><strong>Abstract.</strong> In 2016, the Municipality of Bologna (Italy) has undertaken the restoration of one of the symbols of the entire city, the Fountain of Neptune, in evident state of degradation. The works have touched upon all the aspects of this complex object and the project has seen involved the Municipality and the University of Bologna, the Istituto Superiore per la Conservazione e il Restauro (ISCR) (Rome) and the Visual Computing Lab of the CNR – ISTI (Pisa), in a modern and highly multi-disciplinary approach.</p><p>One of the key elements of the project was made up by the creation of an information system ad hoc developed to permit, in an innovative, efficient and user-friendly way, the collection, sharing, management and analysis of all the information and data related to diagnostics and restoration actions. The base of the information system is a very detailed 3D model of the monument, realized by means of the most modern techniques for objects 3D modelling (laser scanning, digital photogrammetry and 3D scanning) integrated together with the aim to obtain a photo-textured 3D model characterized by a sub-millimetre precision level in the geometric description and a high perceptive fidelity of colour reproduction.</p><p>The surveying activities and data processing, performed by the DICAM Geomatics group of the University of Bologna (with the collaboration of the MCM Company of Rome), are described in the paper, with considerations on the problems encountered and the procedures and solutions adopted. The information system has been developed by CNR-ISTI.</p>

scholarly journals 2½-minute 3D 7T 31P-MRSI of the human heart using concentric rings (CRT)

2021 ◽  
Author(s):  
William T Clarke ◽  
Lukas Hingerl ◽  
Bernhard Strasser ◽  
Wolfgang Bogner ◽  
Ladislav Valkovic ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Variable Number ◽  
Low Rank ◽  
Acquisition Time ◽  
Temporal Data ◽  
Scan Time ◽  
Spread Function ◽  
3D Acquisition ◽  
Spatio Temporal ◽  
31P Mrsi

A 3D density-weighted concentric ring trajectory (CRT) MRSI sequence is implemented for cardiac 31P-MRS at 7T. The point-by-point k-space sampling of traditional phase-encoded CSI sequences severely restricts the minimum scan time at higher spatial resolutions. Our proposed CRT sequence implements a stack of concentric rings trajectory, with a variable number of rings and planes spaced to optimise the density of k-space weighting. This creates flexibility in acquisition time, allowing acquisitions substantially faster than traditional phase-encoded CSI sequences, while retaining high SNR. We first characterise the signal-to-noise ratio and point spread function of the CRT sequence in phantoms. We then evaluate it at five different acquisition times and spatial resolutions in the hearts of five healthy participants at 7T. These different sequence durations are compared with existing published 3D acquisition-weighted CSI sequences with matched acquisition times and spatial resolutions. To minimise the effect of noise on the short acquisitions, low-rank denoising of the spatio-temporal data was also performed after acquisition. The proposed sequence measures 3D localised PCr/ATP ratios of the human myocardium in 2.5 minutes, 2.6 times faster than the minimum scan time for the acquisition-weighted phase-encoded CSI. Alternatively, in the same scan time a 1.7-times smaller nominal voxel volume can be achieved. Low-rank denoising reduced the variance of measured PCr/ATP ratios by 11% across all protocols. The faster acquisitions permitted by 7T CRT 31P-MRSI could make cardiac stress protocols or creatine kinase rate measurements (which involve repeated scans) more tolerable for patients without sacrificing spatial resolution.

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