Virtual Reality Solutions Employing Artificial Intelligence Methods: A Systematic Literature Review

被引:4
|
作者
de Oliveira, Taina Ribeiro [1 ]
Rodrigues, Brenda Biancardi [1 ]
da Silva, Matheus Moura [1 ]
Spinasse, Rafael Antonio N. [1 ]
Ludke, Gabriel Giesen [1 ]
Soares Gaudio, Mateus Ruy [1 ]
Rocha Gomes, Guilherme Iglesias [1 ]
Cotini, Luan Guio [1 ]
Vargens, Daniel da Silva [1 ]
Schimidt, Marcelo Queiroz [1 ]
Andreao, Rodrigo Varejao [1 ]
Mestria, Mario [1 ]
机构
[1] Inst Fed Espirito Santo Ifes, Campus Vitoria Av Vitoria 1729, BR-29040780 Vitoria, ES, Brazil
关键词
Virtual reality; artificial intelligence; Industry; 4.0; literature review; IMAGE RECOGNITION; WIRELESS NETWORKS; DIGITAL-TWIN; LEARNING FRAMEWORK; FEATURE-EXTRACTION; DEEP; VR; CLASSIFICATION; ALGORITHM; 360-DEGREES;
D O I
10.1145/3565020
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Although there are methods of artificial intelligence (AI) applied to virtual reality (VR) solutions, there are few studies in the literature. Thus, to fill this gap, we performed a systematic literature review of these methods. In this review, we apply a methodology proposed in the literature that locates existing studies, selects and evaluates contributions, analyses, and synthesizes data. We used Google Scholar and databases such as Elsevier's Scopus, ACM Digital Library, and IEEE Xplore Digital Library. A set of inclusion and exclusion criteria were used to select documents. The results showed that when AI methods are used in VR applications, the main advantages are high efficiency and precision of algorithms. Moreover, we observe that machine learning is the most applied AI scientific technique in VR applications. In conclusion, this paper showed that the combination of AI and VR contributes to new trends, opportunities, and applications for human-machine interactive devices, education, agriculture, transport, 3D image reconstruction, and health. We also concluded that the usage of AI in VR provides potential benefits in other fields of the real world such as teleconferencing, emotion interaction, tourist services, and image data extraction.
引用
收藏
页数:29
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