Department of Computer Science and Engineering
University of Washington

Multimedia Information Retrieval

This research is supported by the National Science Foundation under grant number DBI-0543631. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarly reflect the views of the National Science Foundation.

Project Summary:

Scientific research in the biological domain generates massive amounts of data of many different kinds. With a hypothesis to investigate, researchers run large numbers of experiments that use data from human and animal subjects and produce multiple outputs of different modalities ranging from simple textual data, to signal, image, and 3D volumes such as CT and MRI scans.In spite of the massive scale and complexity, many researchers at the forefront of biological sciences are using antiquated methods for storing their multimedia data. Data are often kept in multiple locations including computers, notebooks, and file drawers.

The goal of this research is to develop a unified methodology for organization and retrieval of biological data from scientific experiments. Our work builds on existing work in experiment management, approximate queries, and content-based image retrieval. We are developing a query framework for multimedia data that provides users with a unified way to access multiple types of data. Queries will be able to handle both single data types and multiple related data types, such as registered CT and MRI scans or neuronal firing patterns and related fMRI data. The data will be organized in a way that is both easy for users to understand and efficient query access. A prototype system will be built and evaluated on thee different applications: a study of language sites in the human brain, an analysis of the relationship of cataract formation to genetic factors, and a study of craniofacial disorders in children.

People:

Linda Shapiro, PI	James Brinkley, co-PI	Dan Suciu, co-PI	Sara Rolfe, RA

Indriyati Atmosukarto, RA	Jia Wu, RA	Lynn Yang, RA	Kasia Wilamowska, RA

Collaborators:

Ravensara Travillian	John Clark	Michael Cunningham	Carrie Heike	Rosalia Tungaraza

Eye and Skull Shape Demos

Publications:

M. Gubanov, A. Pyayt, L. G. Shapiro, "ReadFast: Browsing large documents through Unified Famous Objects," Proceedings of the 12th IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, Nevada, 2011.

M. Gubanov, L. G. Shapiro, A. Pyayt, "Learning Unified Famous Objects (UFO) to Bootstrap Information Integration," Proceedings of the 12th IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, Nevada, 2011.

I. Atmosukarto, L. G. Shapiro, C. Heike, "Use of Genetic Programming for Learning 3D Craniofacial Shape Quantification", ICPR 2010.

I. Atmosukarto and L. G. Shapiro, "3D Object Retrieval Using Salient Views", ACM Multimedia Information Retrieval, 2010.

I. Atmosukarto, L. G. Shapiro, J. R. Starr, C. L. Heike, B. Collett, M. L. Cunningham, M. L. Speltz, "3D Head Shape Quantification for Infants with and without Deformational Plagiocephaly", The Cleft-Palate Craniofacial Journal, 2009.

I. Atmosukarto, K. Wilamowska, C. Heike, L. G. Shapiro. "3D Object Classification using Salient Point Patterns With Application to Craniofacial Research, Pattern Recognition, Vol. 43, No. 4, 2010, pp. 1502-1517.

R. F. Tungaraza, J. Guan, L. G. Shapiro, J. F. Brinkley, J. Ojemann, and J. D. Franklin, "A Similarity Retrieval Tool for Functional Magnetic Resonance Imaging (fMRI) Statistical Maps," Artificial Intelligence in Medicine, to appear 2009.

R. F. Tungaraza, J. Guan, S. Rolfe, I. Atmosukarto, A. Poliakov, N. M. Kleinhans, E. Aylward, J. Ojemann, J. F. Brinkley, L. G. Shapiro, "A Similarity Retrieval Method for Functional Magnetic Resonance Imaging (fMRI) Statistical Maps," SPIE Medical Imaging: Image Processing, 2009.

L Shapiro, K Wilamowska, I Atmosukarto, J Wu, CL Heike, M Spelz, and M Cunningham. "Shape-Based Classification of 3D Head Data." International Conference on Image Analysis and Processing, 2009.

J. Wu, K. Wilamowska, L. Shapiro, C. Heike, "Automatic Analysis of Local Nasal Features in 2q11.2DS Affected Individuals," IEEE EMBS, 2009.

K Wilamowska, L Shapiro, and CL Heike. "Quantification of 3D face shape in 22q11.2 deletion syndrome". IEEE International Symposium on Biomedical Imaging, 2009.

S. M. Rolfe, L. Finney, R. F. Tungaraza, J. Guan, L.G. Shapiro, J.F. Brinkely, A. Poliakov, N. Kleinhans, E. Alyward, "An independent component analysis based tool for exploring functional connections in the brain," SPIE Medical Imaging: Image Processing, 2009.

I. Atmosukarto, L. Shapiro, M. Cunningham, and M. Speltz. "Automatic 3D Shape Severity Quantification and Localization for Deformational Plagiocephaly". In Proc. SPIE Medical Imaging: Image Processing, 2009.

S.Yang, I. Atmosukarto, J. Franklin, J. F. Brinkley, D. Suciu, and L. G. Shapiro,"A Model of Multimodal Fusion for Medical Applications," SPIE Multimedia Content Access: Algorithms and Systems III, 2009.