
Image Information System research project
Development activities
The group's major projects:
Progressive
Content-based Image Retrieval: This project is jointly
funded by NASA/IBM.
The main challenges are:
- a scalable framework which allows the system to scale to
- large amount of data (accumulated at the rate greater than
terabytes/week),
- large amount of features (not much less than the amount of data),
and
- large number of users;
- an extensible content-based query framework which allows
- user defined features (in addition to texture,
spectral histogram, and shape),
- user defined objects (at the semantic, feature or pixel level),
and
- composite objects (using spatial, temporal, or boolean relationship).
Our proposed solution includes:
- progressive data representation based on a combination wavelet
transformation and entropy coding;
- progressive feature extraction;
- progressive semantic extraction (supervised or
unsupervised classification);
- progressive search at the semantic, feature and the pixel levels.
Our intended applications include:
Please take a look at our
demo system
and the
white paper.
Interactive Query Construction: This project tries to
address three emerging issues faced by the multimedia
applications with unstructured data (such as time series, images, and video)
in a client/server environment:
- Interactive query construction: the necessary information
regarding to the valid query syntax
schema, attributes, valid data range is available
to the user right before the user needs it,
- Query parsing offloading: the client (usually written
in Java) performs as much as possible the checking of the syntax and semantics
(YES! semantics) of the query.
- Extensible query environment: where the user can incorporate
user defined features, user defined objects and composite objects
using the same query framework (just like SQL).
- Iterative refinement: the user can easily incoporate both
previous queries and query results into a new query.
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