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Applied Sciences
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Recent Advances in 3D Reconstruction, 3D Imaging and Virtual Reality
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Recent Advances in 3D Reconstruction, 3D Imaging and Virtual Reality

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 1488

Special Issue Editor

Prof. Dr. Oleg Lobachev

E-Mail Website
Guest Editor
Leibniz Fachhochschule School of Business, Expo Plaza 11, 30539 Hannover, Germany
Interests: 3D reconstruction; virtual reality; visual computing

Special Issue Information

Dear Colleagues,

The subject of 3D imaging is very important in, but not limited to, modern medicine. The process of 3D reconstruction and the acquisition of 3D data are inherent parts of 3D imaging and have been used to obtain data in some, previously classical, 2D modalities. Examples include capturing 3D scenes, and obtaining 3D data from a series of 2D images, e.g., from histological images in medicine, as well as further advances in CT volume construction.

Virtual reality is used as a vehicle to convey full 3D information to the viewer. It has a lot of potential in combination with 3D imaging.

We are welcoming contributions related to the topics below:

  • 3D reconstruction;
  • 3D histology;
  • Sensor fusion;
  • Computed tomography;
  • Volumetric data;
  • Virtual reality;
  • Augmented reality;
  • Visual computing.

Prof. Dr. Oleg Lobachev
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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.

Keywords

  • 3D reconstruction
  • 3D histology
  • sensor fusion
  • computed tomography
  • volumetric data
  • virtual reality
  • augmented reality
  • visual computing

Published Papers (2 papers)

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Research

16 pages, 14619 KiB  
Article
Virtual Reality in Cultural Heritage: A Setup for Balzi Rossi Museum
by Saverio Iacono, Matteo Scaramuzzino, Luca Martini, Chiara Panelli, Daniele Zolezzi, Massimo Perotti, Antonella Traverso and Gianni Viardo Vercelli
Appl. Sci. 2024, 14(9), 3562; https://doi.org/10.3390/app14093562 - 23 Apr 2024
Viewed by 289
Abstract
This study presents the creation of a virtual reality experience for the Museo Preistorico dei Balzi Rossi e Zona Archeologica (hence Balzi Rossi Museum) commemorating the centenary of Prince Albert I Grimaldi’s archaeological work at the site. The project aims to preserve and [...] Read more.
This study presents the creation of a virtual reality experience for the Museo Preistorico dei Balzi Rossi e Zona Archeologica (hence Balzi Rossi Museum) commemorating the centenary of Prince Albert I Grimaldi’s archaeological work at the site. The project aims to preserve and convey the site’s heritage through advanced VR technology. Photogrammetry was used for 3D reconstruction of the entire Balzi Rossi coastal cliffs, including the notable “Caviglione” and “Florestano” caves, known for their upper Paleolithic rock engravings. Two subsequent development phases produced the final public VR experience, incorporating Nanite technology for enhanced visual fidelity. This advancement resulted in a more detailed and immersive VR experience, presenting the Balzi Rossi cliffs across different historical periods, including the Würm glaciation. Key to this phase was optimizing the VR experience for performance, focusing on stable frame rates and minimizing motion sickness, and integrating a multi-lingual interface for broader accessibility. Since November 2023, the VR setup at Balzi Rossi Museum has been an educational and interactive feature enabling visitors to virtually explore the site’s history. This study aims to describe a process for optimizing and enabling the creation of VR experiences while maintaining a high polygon count within the context of small teams. Full article
(This article belongs to the Special Issue Recent Advances in 3D Reconstruction, 3D Imaging and Virtual Reality)
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22 pages, 6902 KiB  
Article
Bi-Resolution Hash Encoding in Neural Radiance Fields: A Method for Accelerated Pose Optimization and Enhanced Reconstruction Efficiency
by Zixuan Guo, Qing Xie, Song Liu and Xiaoyao Xie
Appl. Sci. 2023, 13(24), 13333; https://doi.org/10.3390/app132413333 - 18 Dec 2023
Viewed by 915
Abstract
NeRF has garnered extensive attention from researchers due to its impressive performance in three-dimensional scene reconstruction and realistic rendering. It is perceived as a potential pivotal technology for scene reconstruction in fields such as virtual reality and augmented reality. However, most NeRF-related research [...] Read more.
NeRF has garnered extensive attention from researchers due to its impressive performance in three-dimensional scene reconstruction and realistic rendering. It is perceived as a potential pivotal technology for scene reconstruction in fields such as virtual reality and augmented reality. However, most NeRF-related research and applications heavily rely on precise pose data. The challenge of effectively reconstructing scenes in situations with inaccurate or missing pose data remains pressing. To address this issue, we examine the relationship between different resolution encodings and pose estimation and introduce BiResNeRF, a scene reconstruction method based on both low and high-resolution hash encoding modules, accompanied by a two-stage training strategy. The training strategy includes setting different learning rates and sampling strategies for different stages, designing stage transition signals, and implementing a smooth warm-up learning rate scheduling strategy after the phase transition. The experimental results indicate that our method not only ensures high synthesis quality but also reduces training time. Compared to other algorithms that jointly optimize pose, our training process is sped up by at least 1.3×. In conclusion, our approach efficiently reconstructs scenes under inaccurate poses and offers fresh perspectives and methodologies for pose optimization research in NeRF. Full article
(This article belongs to the Special Issue Recent Advances in 3D Reconstruction, 3D Imaging and Virtual Reality)
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