Computer Vision in Augmented, Virtual, Mixed and Extended Reality environments—A bibliometric review

This work describes a bibliometric analysis of the literature on the use of computer vision algorithms in Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Extended Reality (XR) environments. The analysis aims to highlight the evolution, trends, and effects of research in this field. This review provides an overview of immersive technologies and their applications, as well as the role of computer vision algorithms in enabling these technologies and the potential benefits of using such algorithms. This study identifies important authors, institutions, and research themes by using bibliometric indicators such as citation counts, co-citation analysis, and network analysis. The analysis also identifies gaps and opportunities for additional research in this area, as well as a critical assessment of the quality and relevance of the publications.

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Publication Details

Journal
Visual Informatics
Published
2024-11-21
DOI
https://doi.org/10.1016/j.visinf.2024.11.002
Citations
8
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
1.99

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article

Computer Vision in Augmented, Virtual, Mixed and Extended Reality environments—A bibliometric review

Júlio Castro Lopes, Rui Pedro Lopes
8 citations
Visual Informatics
Augmented Reality Applications
1.99
article

Computer Vision in Augmented, Virtual, Mixed and Extended Reality environments—A bibliometric review

Júlio Castro Lopes, Rui Pedro Lopes
article en
8 citations

Abstract

This work describes a bibliometric analysis of the literature on the use of computer vision algorithms in Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Extended Reality (XR) environments. The analysis aims to highlight the evolution, trends, and effects of research in this field. This review provides an overview of immersive technologies and their applications, as well as the role of computer vision algorithms in enabling these technologies and the potential benefits of using such algorithms. This study identifies important authors, institutions, and research themes by using bibliometric indicators such as citation counts, co-citation analysis, and network analysis. The analysis also identifies gaps and opportunities for additional research in this area, as well as a critical assessment of the quality and relevance of the publications.

Visual InformaticsVol. 8(4)
Universidade Politécnica de Bragança (PT), Research Centre in Digitalization and Intelligent Robotics (PT)
Fundação para a Ciência e a Tecnologia, European Regional Development Fund
Openalex Percentile: Top 12%
Augmented Reality Applications
1.99
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