DIGITAL CLAY MODELING WITH AI-ASSISTED FEEDBACK
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6899Keywords:
AI-Assisted Sculpting, Digital Clay Modeling, Geometry-Aware Neural Networks, 3D Shape Analysis, Interactive Feedback Systems, Creative AI ToolsAbstract [English]
Digital clay modeling has become a paradigm shift in sculptural design in that the users are able to work with digital materials in a way never before possible, with control and fluidity never seen. Many conventional digital sculpture has a workflow, however, that does not provide smart feedback, which facilitates refining, aesthetic refinement, and technical precision. In this paper, a proposal of an AI-based digital clay modeling system will be presented, encompassing geometry-sensitive neural networks, multimodal feature detection, and user-AI feedback mechanisms that can be used to strengthen the process of sculptural creation. The 3D mesh, voxel and implicit surface representations are included in the system architecture to enable the feedback engine to assess deformable geometries in real time. Convolutional neural networks (CNNs), graph neural networks (GNNs), and implicit models are used to capture structural, topological and stylistic representations that are required to provide accurate feedback. The proposed feedback engine considers three major dimensions: (1) identification of sculpting anomalies including asymmetry, instability, and unintentional deformations; (2) aesthetic guidance based on maximization of proportion, balance, flow of curvature and stylistic consistency; and (3) adaptive guidance according to skill level of the user where the beginner, intermediate, and expert users have the ability to receive context-sensitive guidance. It is evaluated by benchmark 3D modeling datasets and own sequences of clay deformation and it shows better accuracy of anomaly detection and higher modeling fluency.
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Copyright (c) 2025 Tarun Kapoor, Neha, Subramanian Karthick, Dr. S. Prince Mary, S. Simonthomas, Kajal Thakuriya
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