Research
Result

Annual research result

MUCH Annual Plans

MUCH (Multi-purpose Universal Cultural Heritage) Annual Utilization Plans

MUCH 3rd year research results

MUCH Platform

Implementation of AI research results and functions

3D Gaussian Splatting

Intelligent Relationship-Based Visualization

MUCH Knowledge Graph

AI-based route guidance

'Bangasayusang' demonstration content

MUCH 2nd year research results

AI model-based cultural heritage correlation and recommendation image classification system

Intelligent Cultural Heritage Platform

Data exploration method using knowledge graph

Results of utilizing artificial intelligence based on cultural heritage

MUCH 1st year research results

W3C Semantic Web standard configuration design

  • Design of standard configuration for storing unstructured and unrefined digital data

Conversion and management DB configuration design

  • Standard configuration design for storing unstructured and unrefined digital data Conversion and management DB configuration design for existing digital data
  • Creation of cultural heritage 3D asset production guidelines

Data type classification technology

  • Considering cross-reference relationships between heterogeneous data, we design the structure of relationships and metadata to visualize connections between data and relationships between cultural heritage.

Metadata design

  • Classification/tagging and relationship definition in cultural heritage digital data systems
Result5

Visualization of hierarchical structure-based classification data relationships

  • Design of a data structure based on a 3-level hierarchy with an added Project Level considering the data characteristics of the National Museum of Korea

Development of cultural heritage visualization service​

  • Development of services such as keyword search, catalog-based data exploration, and open shared data SPARQL

Archive-based data visualization

  • Develop research and pilot services on effective visualization methods for cultural heritage archive data

Development of image conversion technology

  • Development of cultural heritage image conversion algorithm based on Convolutional Neural Network

Optimizing cultural heritage asset data

  • Acquisition work for asset data has been conducted on 56 artifacts (66 items), obtaining 3D assets (50 artifacts, 60 items), RTI (10 artifacts, 15 items), and gigapixel images (5 artifacts, 5 items)
  • Recompress gITF format to Nexus format for optimization in various environments

Past Project view

Development of Intelligent Curation and Service Platform based Digital Asset for Immersive Cultural Heritage

CHIC(Cultural Heritage Intelligent Curation)

Homepage

MUCH

Leading the digital standardization of cultural heritage, 

the Intelligent Heritage Sharing Platform.

MUCH(Multi-purpose Universal Cultural Heritage)

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