A Study on the Next-Generation 3D Modeling Pipeline through the Integration of Generative AI and Photogrammetry

• 발행기관: 한국컴퓨터게임학회
• 저자명: Ki-Don PARK Ji-Hoon AHN Young-A YI
• 간행물 정보: 『한국컴퓨터게임학회논문지』제38권 1호, 26~35쪽, 전체 10쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2025.03.31

국문 초록

This study proposes and verifies a next-generation 3D modeling pipeline integrating Generative AI and Photogrammetry techniques. Two types of objects were selected for experimentation: a bust combining characteristics of both objects and characters, and a stone slab exhibiting planar and symmetrical features. Firstly, videos depicting these objects from various viewpoints were generated using generative AI models. Secondly, these videos were processed through Photogrammetry software to produce high-quality 3D meshes and diffuse textures. Lastly, post-processing including high and Low-polygon mesh separation, UV unwrapping, and texture baking was performed, successfully producing Physically Based Rendering (PBR)-compatible game assets. The proposed pipeline demonstrates significant potential for practical applications across various industries, and further advances in generative AI and future research are expected to broaden this novel approach to digital asset creation.

목차

1. 서론

2. 이론적 배경

3. 생성형 AI와 사진측량 기술을 결합한 3D 그래픽 데이터 제작

4. 연구 결과 및 제안

5. 결 론

참고문헌

키워드

Generative AI Photogrammetry 3D Scanning Game Graphics