This study proposes a real-time content design pipeline optimized for Unreal Engine, integrating generative AI-based image creation with AI-assisted 3D modeling tools. The pipeline aims to streamline the production of high-quality assets for real-time applications, including games and simulations. Two types of subjects were selected: a bust combining organic character features, and a stone slab characterized by planar and symmetrical structure. Multi-angle image data were first synthesized using advanced generative AI models to simulate diverse viewpoints. These were then processed using AI-enhanced photogrammetry and modeling tools to reconstruct detailed 3D meshes and extract base textures. Post-processing steps, including mesh decimation, UV unwrapping, and texture baking, were performed to ensure compatibility with Physically Based Rendering (PBR) workflows used in Unreal Engine. The final assets were successfully imported into Unreal Engine, demonstrating visual fidelity and performance suitability in a real-time environment. The study confirms the pipeline’s potential for accelerating asset development and suggests promising future directions in AI-driven digital content creation.

ABSTRACT
1. 서론
    1.1 연구의 배경 및 필요성
    1.2 연구의 목적 및 범위
2. 관련 연구
    2.1 생성형 AI를 활용한 이미지 및 콘텐츠 생성 기술
    2.2 AI 모델링 도구를 활용한 3D 모델링 자동화
    2.3 Unreal Engine을 활용한 실시간 콘텐츠 디자인 연구
3. 연구 파이프라인
    3.1 텍스트 프롬프트 기반 이미지 생성
    3.2 이미지 기반 3D 모델링 자동화 (AI 모델링 도구 기반)
    3.2 3D 오브젝트의 Unreal Engine 배치
    3.4 전체 파이프라인의 흐름 요약
4. 이미지 생성 및 3D 모델링 자동화
    4.1 텍스트 프롬프트 설계 및 이미지 생성 알고리즘
    4.2 이미지 기반 구조 분석 및 파라미터 추출
    4.3 AI 기반 자동 3D 모델링 프로세스
    4.4 자동화 파이프라인의 특징과 공학적 의의
5. 결론
참고문헌

• Ok-Hue Cho(Department of Animation, College of Convergence Engineering, 20 , Hongjimun 2-gil, Sangmyung University, Jongno-gu, Seoul, Korea) | 조옥희 Corresponding author