The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascen...The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.展开更多
Computational aesthetics,which bridges science and art,is emerging as a new interdisciplinary field.This paper concentrates on two main aspects of computational aesthetics:aesthetic measurement and quantification,gene...Computational aesthetics,which bridges science and art,is emerging as a new interdisciplinary field.This paper concentrates on two main aspects of computational aesthetics:aesthetic measurement and quantification,generative art,and then proposes a design generation framework.On aesthetic measurement and quantification,we review different types of features used in measurement,the currently used evaluation methods,and their applications.On generative art,we focus on both fractal art and abstract paintings modeled on well-known artists’styles.In general,computational aesthetics exploits computational methods for aesthetic expressions.In other words,it enables computer to appraise beauty and ugliness and also automatically generate aesthetic images.Computational aesthetics has been widely applied to many areas,such as photography,fine art,Chinese hand-writing,web design,graphic design,and industrial design.We finally propose a design generation methodology,utilizing techniques from both aesthetic measurements and generative art.展开更多
文摘The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.
基金supported by the National Social Science Fund Art Project(No.17BG134)Natural Science Foundation of the Beijing Municipal Education Committee(No.KM201710050001)+1 种基金National NSFC project(Grant number 61772463)National NSFC project(Grant number 61572348).
文摘Computational aesthetics,which bridges science and art,is emerging as a new interdisciplinary field.This paper concentrates on two main aspects of computational aesthetics:aesthetic measurement and quantification,generative art,and then proposes a design generation framework.On aesthetic measurement and quantification,we review different types of features used in measurement,the currently used evaluation methods,and their applications.On generative art,we focus on both fractal art and abstract paintings modeled on well-known artists’styles.In general,computational aesthetics exploits computational methods for aesthetic expressions.In other words,it enables computer to appraise beauty and ugliness and also automatically generate aesthetic images.Computational aesthetics has been widely applied to many areas,such as photography,fine art,Chinese hand-writing,web design,graphic design,and industrial design.We finally propose a design generation methodology,utilizing techniques from both aesthetic measurements and generative art.
