Grant Number: IIS- 0219272 Institution of PI: The Pennsylvania State Univ. PIs: James Z. Wang, Jia Li Title: Advancing Digital Imagery Technologies for Asian Art and Cultural Heritages This collaborative research project aims at advancing information technologies related to the retrieval and dissemination of digital imagery for Asian art and cultural heritages. The research team at Penn State work closely with collaborators from several other institutions. Technologies are being developed for browsing, managing, and searching large collections of high quality art images. Methodologies in statistical learning and data mining are explored to automatically learn from multi-modal data including images and manual annotations. On the educational front, several undergraduate honors students are funded through the project. They work with faculty and graduate students on research topics. • Interdisciplinary collaboration: Enabling the technology researchers to broaden their knowledge by collaborating across disciplines. • Human development: The project provided invaluable research experience to the graduate and undergraduate honors students. One Ph.D student supported through this project is now a tenure-track faculty member. Several undergraduate honors students are working closely with faculty members of this project in the state-of-the-art research lab. • Dissemination: Technologies developed during the project have been demonstrated over the Web and attracted thousands of unique users monthly. The SIMPLIcity system has been sought after and obtained by more than 60 institutions for research and education. • Applications: Methodologies developed have been applied to other areas including satellite image analysis (NGA project). Broader impacts: Significant Results: Graphic: Research Objectives: Approach: Stroke style based retrieval Developed an approach to analyze stroke/brush styles of fine art paintings by spatial stochastic modeling. Developed ALIP (Automatic Linguistic Indexing of Pictures) system. Extended MIL to the problem of region-based image categorization. Publications: 9 papers in high impact journals [JMLR, IEEE Trans PAMI, IEEE Trans IP, IJODL, IEEE Trans Fuzzy Systems], more than 10 papers in international conferences, and one monograph. Collaboration with NSF/IDLP Global Memory Net PIs with honors undergraduate researchers

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Grant Number: IIS- 0219272 Institution of PI: The Pennsylvania State Univ. PIs: James Z. Wang, Jia LiTitle: Advancing Digital Imagery Technologies for Asian Art and Cultural Heritages

This collaborative research project aims at advancing information technologies related to the retrieval and dissemination of digital imagery for Asian art and cultural heritages. The research team at Penn State work closely with collaborators from several other institutions.

Technologies are being developed for browsing, managing, and searching large collections of high quality art images. Methodologies in statistical learning and data mining are explored to automatically learn from multi-modal data including images and manual annotations. On the educational front, several undergraduate honors students are funded through the project. They work with faculty and graduate students on research topics.

• Interdisciplinary collaboration: Enabling the technology researchers to broaden their knowledge by collaborating across disciplines.

• Human development: The project provided invaluable research experience to the graduate and undergraduate honors students. One Ph.D student supported through this project is now a tenure-track faculty member. Several undergraduate honors students are working closely with faculty members of this project in the state-of-the-art research lab.

• Dissemination: Technologies developed during the project have been demonstrated over the Web and attracted thousands of unique users monthly. The SIMPLIcity system has been sought after and obtained by more than 60 institutions for research and education.

• Applications: Methodologies developed have been applied to other areas including satellite image analysis (NGA project).

Broader impacts:

Significant Results:

Graphic:

Research Objectives:

Approach:

Stroke style based retrieval

Developed an approach to analyze stroke/brush styles of fine art paintings by spatial stochastic modeling. Developed ALIP (Automatic Linguistic Indexing of Pictures) system. Extended MIL to the problem of region-based image categorization. Publications: 9 papers in high impact journals [JMLR, IEEE Trans PAMI, IEEE Trans IP, IJODL, IEEE Trans Fuzzy Systems], more than 10 papers in international conferences, and one monograph.

Collaboration with NSF/IDLP Global Memory Net

PIs with honors undergraduate researchers