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

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