AI-based experts’ knowledge visualization of cultural heritage: A case study of Terracotta Warriors

• This study constructs a dataset of Terracotta Warriors from Pit No. 1, encompassing 10 attributes of 1,087 warriors. • Various AI-based methods are employed to augment and process the dataset, enabling the extraction of key attribute information. • Several visualization techniques are utilized to visually interpret experts’ knowledge of cultural heritage. Advancements in 3D modeling, digital display technologies, and the growing availability of digital cultural heritage data have significantly improved the accuracy of heritage depictions and expanded opportunities for analysis. However, while many studies focus on presenting specific cultural heritage figurines, an often overlooked aspect is the visualization of the Terracotta Warriors as a unified entity. This involves concisely representing the distribution of features and their relationships, providing a clear and insightful presentation that engages practitioners, academics, and wider audiences. To tackle the challenges mentioned above, this research seeks to explore the application of AI methods in processing cultural heritage data. It aims to optimize and augment the dataset, analyze the distribution and relationships of various attributes, and interpret the analysis results through visualization techniques. The Terracotta Warriors, among China’s most significant cultural heritages and renowned for their abundance, exquisite workmanship, and magnitude, are chosen as a case study . The contribution of this paper is primarily twofold. Firstly, we constructed a dataset of Terracotta Warriors from Pit No. 1, detailing the attributes significant for identifying different Terracotta Warriors. Secondly, we employ various AI methods, such as generative adversarial network(GAN) and random forest , to process and analyze these attributes, followed by visualizing the analysis results for an intuitive presentation. This study introduces a novel scheme for presenting information on a collection of cultural relics, offering a practical case for analyzing and visualizing the Terracotta Warriors’ attributes as a whole entity, rather than showcasing individual relics’ information in isolation. This approach can be applied to other cultural heritage artifacts, such as Chinese ceramics, and supports further multidisciplinary research , including AI-based cultural heritage analysis, processing, and presentation.

Authors

Institutions

Publication Details

Journal
Journal of Cultural Heritage
Published
2025-01-29
DOI
https://doi.org/10.1016/j.culher.2025.01.006
Citations
5
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
11.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-based experts’ knowledge visualization of cultural heritage: A case study of Terracotta Warriors

Yue Jiang, Yuhe Zhang, Bowen Jing, Siyi Li et al.
5 citations
Journal of Cultural Heritage
3D Surveying and Cultural Heritage
11.73
article

AI-based experts’ knowledge visualization of cultural heritage: A case study of Terracotta Warriors

Yue Jiang, Yuhe Zhang, Bowen Jing, Siyi Li, Liujie Yang
article en
5 citations

Abstract

• This study constructs a dataset of Terracotta Warriors from Pit No. 1, encompassing 10 attributes of 1,087 warriors. • Various AI-based methods are employed to augment and process the dataset, enabling the extraction of key attribute information. • Several visualization techniques are utilized to visually interpret experts’ knowledge of cultural heritage. Advancements in 3D modeling, digital display technologies, and the growing availability of digital cultural heritage data have significantly improved the accuracy of heritage depictions and expanded opportunities for analysis. However, while many studies focus on presenting specific cultural heritage figurines, an often overlooked aspect is the visualization of the Terracotta Warriors as a unified entity. This involves concisely representing the distribution of features and their relationships, providing a clear and insightful presentation that engages practitioners, academics, and wider audiences. To tackle the challenges mentioned above, this research seeks to explore the application of AI methods in processing cultural heritage data. It aims to optimize and augment the dataset, analyze the distribution and relationships of various attributes, and interpret the analysis results through visualization techniques. The Terracotta Warriors, among China’s most significant cultural heritages and renowned for their abundance, exquisite workmanship, and magnitude, are chosen as a case study . The contribution of this paper is primarily twofold. Firstly, we constructed a dataset of Terracotta Warriors from Pit No. 1, detailing the attributes significant for identifying different Terracotta Warriors. Secondly, we employ various AI methods, such as generative adversarial network(GAN) and random forest , to process and analyze these attributes, followed by visualizing the analysis results for an intuitive presentation. This study introduces a novel scheme for presenting information on a collection of cultural relics, offering a practical case for analyzing and visualizing the Terracotta Warriors’ attributes as a whole entity, rather than showcasing individual relics’ information in isolation. This approach can be applied to other cultural heritage artifacts, such as Chinese ceramics, and supports further multidisciplinary research , including AI-based cultural heritage analysis, processing, and presentation.

Journal of Cultural HeritageVol. 72
Northwest University (CN), Shaanxi History Museum (CN)
Sustainable cities and communities
Openalex Percentile: Top 2%
3D Surveying and Cultural Heritage
11.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.