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Updated: Jan 10, 2026

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

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Published on: March 11, 2021

Calli-VA: A Visual Analytics System for Analyzing and Comparing Chinese Calligraphic Styles.

Jincheng Li, Jinpeng Wu, Shaocong Tan

IEEE Transactions on Visualization and Computer Graphics

|November 21, 2025

Summary

This summary is machine-generated.

Calli-VA, a visual analytics system, aids in analyzing Chinese calligraphy styles. It overcomes limitations of traditional methods, offering systematic character analysis and pattern discovery for cultural heritage insights.

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Area of Science:

Digital Humanities
Art History
Computer Science

Background:

Chinese calligraphy is a vital part of cultural heritage, offering insights into ancient China.
Analyzing calligraphic styles is complex due to qualitative method limitations and quantitative approach issues.
Existing methods lack scalability and can be inconsistent or difficult to use.

Purpose of the Study:

To introduce Calli-VA, a visual analytics system designed for analyzing Chinese calligraphy.
To address the challenges of scalability, consistency, usability, and misalignment in calligraphic style analysis.
To enhance the appreciation, learning, and advancement of Chinese calligraphy.

Main Methods:

Calli-VA extracts character images and stroke data from original works.
It systematically characterizes each character based on defined criteria.
The system integrates overview, relationship discovery, explanation, and recommendation mechanisms.

Main Results:

Calli-VA provides a scalable and systematic approach to analyzing calligraphic styles.
The system facilitates pattern discovery and understanding of relationships between characters.
Integrated features aid in user exploration, documentation, and sharing of findings.

Conclusions:

Calli-VA effectively addresses the limitations of previous methods for analyzing Chinese calligraphy.
The system enhances the study and appreciation of Chinese calligraphic heritage.
Case studies and expert feedback confirm Calli-VA's utility and effectiveness.