Interdisciplinary Research to Advance
Digital Imagery Indexing and
Retrieval Technologies for
Asian Art and Cultural Heritages
James Z. Wang, Jia Li
The Pennsylvania State University, University Park, PA 16802
Ching-chih Chen
Simmons College, Boston, MA 02155
Abstract:
This paper provides an introduction of our NSF-funded research project
on advancing digital imagery technologies for Asian art and cultural
heritages. This international collaborative research project aims at
developing technologies related to the preservation, retrieval, and
dissemination of digital imagery. Researchers in the US, China, and
South Korea will collectively investigate and develop technologies for
acquiring, browsing, managing, and searching large collections of high
quality art images. One of the main research questions the team of US
researchers focuses on is the problem of automatic indexing and
retrieval of digital art images. Building on the foundation of a
successful image retrieval platform, the SIMPLIcity system with the
ALIP algorithm, the team is developing techniques to automatically
associate linguistic terms with image features for indexing Asian art
images. The testbed databases of art images for this research project
in the US will begin by using some of the rich image resources of the
Emperor and the Chinese Memory Net projects by Ching-chih Chen. This image
knowledge base consist of high quality scans, with extensive metadata
information including detailed keyword information, as well as
comprehensive textual descriptions. The research work aims at
demonstrating that (1) modern machine learning and statistical data
mining tools are capable of learning from non-structured or
semi-structured input data such as human annotations, (2) statistical
image modeling techniques can be used in automatic linguistic indexing
and concept dictionary building. Finally, we discuss the challenges
and the importance for the line of interdisciplinary research work.
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Last Modified:
October 3, 2002
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