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J. Imaging
Special Issues
3D Imaging
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3D Imaging

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (28 February 2017)

Special Issue Editors

Prof. Dr. Hassan Ugail

E-Mail Website
Guest Editor
Centre for Visual Computing, University of Bradford, Bradford BD7 1DP, UK
Interests: geometric design; computer graphics; machine learning; visualisation; mathematical modelling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Lihua You

E-Mail Website
Guest Editor
National Centre for Computer Animation, Bournemouth University, Bournemouth BH12 5BB, UK
Interests: geometric modeling; computer animation; computer graphics; image and point cloud-based shape reconstruction; machine learning; applications of ODEs and PDEs in geometric modeling and computer animation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Three-dimensional imaging involves the capture of 3D information, its analysis, display, storage and delivery.  
The following is a list of the main topics covered by this Special Issue. The Issue will, however, not be limited to these topics:
-    3D image processing and analysis techniques, e.g. mesh generation and analysis, surfaces and volumes, segmentation, feature detection, morphological operations, reconstruction, texture and visualisation.  
-    3D image acquisition methods, devices and systems, e.g. point clouds, meshes, laser scanning, photogrammetry, 3D data storage, 3D data exchange.
-    Application areas include, healthcare, biometrics, entertainment (e.g. 3D animation and gaming), CAD/CAM and prototyping, architecture, environment and heritage.

Prof. Hassan Ugail
Dr. Lihua You
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

36587 KiB  
Article
Monitoring of the Nirano Mud Volcanoes Regional Natural Reserve (North Italy) using Unmanned Aerial Vehicles and Terrestrial Laser Scanning
by Tommaso Santagata
J. Imaging 2017, 3(4), 42; https://doi.org/10.3390/jimaging3040042 - 30 Sep 2017
Cited by 8 | Viewed by 4982
Abstract
In the last years, measurement instruments and techniques for three-dimensional mapping as Terrestrial Laser Scanning (TLS) and photogrammetry from Unmanned Aerial Vehicles (UAV) are being increasingly used to monitor topographic changes on particular geological features such as volcanic areas. In addition, topographic instruments [...] Read more.
In the last years, measurement instruments and techniques for three-dimensional mapping as Terrestrial Laser Scanning (TLS) and photogrammetry from Unmanned Aerial Vehicles (UAV) are being increasingly used to monitor topographic changes on particular geological features such as volcanic areas. In addition, topographic instruments such as Total Station Theodolite (TST) and GPS receivers can be used to obtain precise elevation and coordinate position data measuring fixed points both inside and outside the area interested by volcanic activity. In this study, the integration of these instruments has helped to obtain several types of data to monitor both the variations in heights of extrusive edifices within the mud volcano field of the Nirano Regional Natural Reserve (Northern Italy), as well as to study the mechanism of micro-fracturing and the evolution of mud flows and volcanic cones with very high accuracy by 3D point clouds surface analysis and digitization. The large amount of data detected were also analysed to derive morphological information about mud-cracks and surface roughness. This contribution is focused on methods and analysis performed using measurement instruments as TLS and UAV to study and monitoring the main volcanic complexes of the Nirano Natural Reserve as part of a research project, which also involves other studies addressing gases and acoustic measurements, mineralogical and paleontological analysis, organized by the University of Modena and Reggio Emilia in collaboration with the Municipality of Fiorano Modenese. Full article
(This article belongs to the Special Issue 3D Imaging)
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6468 KiB  
Article
Depth Estimation for Lytro Images by Adaptive Window Matching on EPI
by Pei-Hsuan Lin, Jeng-Sheng Yeh, Fu-Che Wu and Yung-Yu Chuang
J. Imaging 2017, 3(2), 17; https://doi.org/10.3390/jimaging3020017 - 21 May 2017
Cited by 9 | Viewed by 6571
Abstract
A depth estimation algorithm from plenoptic images is presented. There are two stages to estimate the depth. First is the initial estimation base on the epipolar plane images (EPIs). Second is the refinement of the estimations. At the initial estimation, adaptive window matching [...] Read more.
A depth estimation algorithm from plenoptic images is presented. There are two stages to estimate the depth. First is the initial estimation base on the epipolar plane images (EPIs). Second is the refinement of the estimations. At the initial estimation, adaptive window matching is used to improve the robustness. The size of the matching window is based on the texture description of the sample patch. Based on the texture entropy, a smaller window is used for a fine texture. A smooth texture requires a larger window. With the adaptive window size, different reference patches based on various depth are constructed. Then the depth estimation compares the similarity among those patches to find the best matching patch. To improve the initial estimation, a refinement algorithm based on the Markov Random Field (MRF) optimization is used. An energy function keeps the data similar to the original estimation, and then the data are smoothed by minimizing the second derivative. Depth values should satisfy consistency across multiple views. Full article
(This article belongs to the Special Issue 3D Imaging)
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6145 KiB  
Article
LaFiDa—A Laserscanner Multi-Fisheye Camera Dataset
by Steffen Urban and Boris Jutzi
J. Imaging 2017, 3(1), 5; https://doi.org/10.3390/jimaging3010005 - 17 Jan 2017
Cited by 15 | Viewed by 10930
Abstract
In this article, the Laserscanner Multi-Fisheye Camera Dataset (LaFiDa) for applying benchmarks is presented. A head-mounted multi-fisheye camera system combined with a mobile laserscanner was utilized to capture the benchmark datasets. Besides this, accurate six degrees of freedom (6 DoF) ground truth poses [...] Read more.
In this article, the Laserscanner Multi-Fisheye Camera Dataset (LaFiDa) for applying benchmarks is presented. A head-mounted multi-fisheye camera system combined with a mobile laserscanner was utilized to capture the benchmark datasets. Besides this, accurate six degrees of freedom (6 DoF) ground truth poses were obtained from a motion capture system with a sampling rate of 360 Hz. Multiple sequences were recorded in an indoor and outdoor environment, comprising different motion characteristics, lighting conditions, and scene dynamics. The provided sequences consist of images from three—by hardware trigger—fully synchronized fisheye cameras combined with a mobile laserscanner on the same platform. In total, six trajectories are provided. Each trajectory also comprises intrinsic and extrinsic calibration parameters and related measurements for all sensors. Furthermore, we generalize the most common toolbox for an extrinsic laserscanner to camera calibration to work with arbitrary central cameras, such as omnidirectional or fisheye projections. The benchmark dataset is available online released under the Creative Commons Attributions Licence (CC-BY 4.0), and it contains raw sensor data and specifications like timestamps, calibration, and evaluation scripts. The provided dataset can be used for multi-fisheye camera and/or laserscanner simultaneous localization and mapping (SLAM). Full article
(This article belongs to the Special Issue 3D Imaging)
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