المؤلفون: Giuseppe Fallacara, Maria Pia Fanti, Fabio Parisi, Nicola Parisi, Valentino Sangiorgio

المساهمون: Giuseppe Fallacara, Maria Pia Fanti, Fabio Parisi, Nicola Parisi and Valentino Sangiorgio, Fallacara, Giuseppe, Fanti, Maria Pia, Parisi, Fabio, Parisi, Nicola, Sangiorgio, Valentino

مصطلحات موضوعية: widely used across various sectors with an unprecedented acceleration in recent years, particularly in the field of image generation. Indeed, such innovation is becoming a paradigmshifting technology in the Architecture, Engineering, and Construction (AEC) sector specifically for the generation of highly detailed and visually compelling images of architectural projects. The AI algorithms, trained on vast datasets, enable users to automatically generate realistic representations of buildings, interiors, and urban landscapes starting from a text string. The potential of these technologies is significant, but the current literature lacks well-defined processes for effectively utilizing these techniques to achieve implementable projects. This paper proposes a novel design approach based on AI-driven Image Generation to support design for digital fabrication, consisting of three steps. Firstly, the conceptual design is defined along with a set of keywords. Secondly, the application of AI in image generation allows designers to efficiently explore a multitude of design possibilities. The AI-based tools facilitate the automatic generation of diverse design variants, aiding professionals in evaluating different options and enhancing their visualizations. Thirdly, by leveraging a synergistic set of techniques including image processing, 3D CAD design, and additive manufacturing, it is possible to transform the images suggested by AI into an actual project that can be effectively fabricated. Finally, the potential of the proposed approach is applied to the case of urban furnishings in historic city centers in southern Italy.

Relation: ispartofbook:CEUR Workshop proceedings; VIPERC 2023: The 2nd International Conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding; numberofpages:12; https://hdl.handle.net/11589/268580

الاتاحة: https://hdl.handle.net/11589/268580