| Issue |
SHS Web Conf.
Volume 194, 2024
The 6th ETLTC International Conference on ICT Integration in Technical Education (ETLTC2024)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 11 | |
| Section | Intelligent Information Design | |
| DOI | https://doi.org/10.1051/shsconf/202419403004 | |
| Published online | 26 June 2024 | |
Semi-automatic A.I.-Specified Stereographic Scene Rendering Techniques Across Various Displays
Spatial Media Group, University of Aizu; Aizu-Wakamatsu, Fukushima 965-8580 ; Japan
* Corresponding author: xilehence@gmail.com
Semi-automatic, A.I.-specified stereographic scene processing is achieved by extending Blender with ChatGPT. We can generate objects and set scenes in Blender semi-automatically by invoking appropriate text prompts. Stereography techniques include anaglyphy, chromastereoscopy, and side-by-side display using binocular viewing. One can create a similar scene by copying and pasting the prompt used. It cannot always work identically, but it behaves roughly the same. First, we established Skybox and added scene Objects (Camera, Cube, etc.) in 3D view, materials, and animation with prompt. Stereographic images are created semiautomatically and compared across some qualities. The goal of this research is to validate those various stereographic techniques as rendered automatically in Blender.
Key words: A.I. / binocular display / ChatGPT / compositing / prompt engineering / rendering / stereography / shading / text-toimage generation
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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