Guest Editors
Dr. Byung-Gyu Kim, Sookmyung Women's University, South Korea.
Dr. Naveen Chilamkurti, La Trobe University, Australia.
Dr. Ji-Woo Kang, Sookmyung Women's University, South Korea.
Summary
In this issue, we aim to explore the application of artificial intelligence (AI) for visual recognition and generation in virtual environments, including issues related to the metaverse and digital twins. Many researchers have a question is "How can AI-based visual recognition and generation improve the realism and interactivity of virtual environments, and what are the implications for the metaverse and digital twins?" AI-based visual recognition and generation can significantly improve the realism and interactivity of virtual environments, and that this technology has the potential to transform the way we interact with virtual worlds, including the creation of more advanced VR/MR, metaverse, and digital twin environments. For this issue, the visual recognition is a crucial element for generating realistic and immersive virtual environments, and the application of AI-based visual recognition technology has the potential to revolutionize the way we create and interact with virtual worlds. Also, some experimental designs with participants and stimuli generated by AI in virtual environments to check the quality of Generative AI should be investigated extensively in terms of the users' responses and perceptions of the stimuli, as well as objective measures of the accuracy and efficiency of the AI-generated visuals.
We expect to find quantitative and qualitative results that demonstrate the potential benefits of AI-based visual recognition and generation for virtual environments, as well as the implications for the development of more advanced VR/MR, metaverse and digital twin environments. Overall, this issue aims to contribute to the growing understanding of AI-based visual recognition and generation for virtual environments, and to provide insights into the potential benefits and issues that arise in more advanced VR/MR, metaverse, and digital twin environments and the potential issues such as ethical concerns and data privacy.
Keywords
The topics are as follows, but not limited to:
Deep visual detection and recognition approaches
Realistic and immersive AI-based generation techniques
Advanced visual expression and recognition for virtual environments
Design of the quality measurement for generated environments
Quality of experience (QoE) and user experience (UX) for AI-generated visuals
Visual interaction techniques for virtual environments
Ethical concerns in virtual environments
Data privacy and security in virtual environments
Advanced VR/MR techniques
Advanced techniques for metaverse and digital twin system
Case study of metaverse service and applications
Case study of digital twins and applications
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