Generating command modeling and design graphs with data augmentation for enhanced 3D modeling support

Abstract

This study proposes a system that automatically generates 3D modeling sequences for various 3D shapes. Existing 3D modeling systems impose a high cognitive load on users, making it particularly difficult for beginners to approach. To address this issue, we developed a system that applies a method for inferring and extracting modeling sequences from 3D shapes to generate Command Modeling and Design Graphs without the need for additional modeling data collection. For this purpose, we reconstructed geometric elements and their structural relationships using a domain-specific language, efficiently modeling shape repetitions and symmetries. The proposed system infers modeling sequences from completed 3D models and converts them into workflow graphs, providing richer and more detailed sequence data compared to existing datasets. As a result, users are expected to significantly improve design efficiency through intuitive modeling processes and command support.