유물 복원 시 인공지능 훈련을 위한 탑 모델링에 관한 연구
A Study on Tower Modeling for Artificial Intelligence Training in Artifact Restoration
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초록
본 논문은 인공지능(AI)을 이용하여 통일신라 석탑인 '경주 불국사 삼층석탑'의 복원을 위해 3D 모델링 과정을 연구했다. 기존의 3D 모델링 방식은 수많은 Verts와 Face를 생성하므로, 이로 인해AI 학습에 상당한 시간이 소요한다. 이에 따라, Verts와 Face의 수를 낮추어 더 효율적인 3D 모델링을 수행하는 방식이 필요하다. 이를 위해, 본 연구에서는 석탑의 구조를 정점 및 면의 수로 분석하고, AI 학습에 최적화된 면수를을 최소화 하도록 모델링 방법을 연구했다. 더불어, 우리나라의 석탑 복원을 위한 인공지능학습에 최적화된 모델링 방법론을 제안하고, 인공지능 학습에 필요한 DataSet 을 확보하는 데 의미가 있다.
Abstract
This paper studied the 3D modeling process for the restoration of the 'Three-story Stone Pagoda of Bulguksa Temple in Gyeongju', a stone pagoda from the Unified Silla Period, using artificial intelligence (AI). Existing 3D modeling methods generate numerous verts and faces, which takes a considerable amount of time for AI learning. Accordingly, a method of performing more efficient 3D modeling by lowering the number of verts and faces is required. To this end, in this study, the structure of the stone pagoda was deeply analyzed and a modeling method optimized for AI learning was studied. In addition, it is meaningful to propose a new 3D modeling methodology for the restoration of stone pagodas in Korea and to secure a data set necessary for artificial intelligence learning.
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