Digital Creation, Representation, and Parametric Style Editing of Chinese Calligraphy

The digitization of Chinese calligraphy is hindered by a prevailing focus on static images, which neglects the art’s essential dynamic brush motion. Mainstream neural network approaches therefore lack the parametric control and interpretability required for practical applications and fail to integrate with process-based brush modeling studies. To resolve these challenges, we introduce a holistic system that represents calligraphy through its dynamic creation process. Our framework unifies a virtual brush model with a structured format that records calligraphy motion data. This process-centric foundation enables our key contribution: parametric calligraphy style editing methods based on motion data that are interactive, explicit, and interpretable. Experimental results validate our system’s ability to faithfully represent and manipulate calligraphy, offering a powerful alternative to static methods. This work establishes a more effective and practical foundation for cultural preservation, interactive education, and artistic expression.