Computer vision meets metaverse

• Published in: Metaverse Vol. 5; no. 1; p. 2464
• Main Authors: Zakynthinou, Vasiliki, Kanakaris, Venetis, Vrochidou, Eleni, Papakostas, George A.
• Format: Journal Article
• Language: English
• Published: 02.02.2024
• ISSN: 2810-9791; 2810-9791
• DOI: 10.54517/m.v5i1.2464

This comprehensive analysis delves into the historical progression and important technological and contemporary advancements of computer vision inside the metaverse. The metaverse, which can be characterized as an interactive virtual reality environment that mirrors the physical world, signifies a novel domain for the utilization of computer vision in various applications. These applications span from object identification and tracking to gesture recognition and augmented reality. Additionally, a thorough evaluation of specific case studies occurs to provide a deeper understanding of the subject. Despite notable progress, the incorporation and utilization of computer vision inside the metaverse present numerous obstacles, including computational expenses, apprehensions regarding data privacy, and the faithful replication of physical aspects of reality. Potential solutions are examined, including deep learning approaches, optimization strategies, and the formation of ethical guidelines. A comprehensive analysis of anticipated patterns within the industry is also included, with emphasis on the confluence of artificial intelligence, the Internet of Things, and blockchain technologies. These convergences are predicted to create substantial prospects for the advancement of the metaverse. This review culminates by offering a contemplation on the ethical considerations and duties that arise from the utilization of computer vision in the realm beyond mortal existence. Research findings demonstrate that these technologies have greatly augmented user engagement and immersion within the digital domain. Readers can enhance their understanding of the interdependent connection between computer vision and the metaverse through the present analysis of existing scholarly works. Thus, this study aspires to make a valuable contribution to the advancement of research in this new domain.