Abstract

The project ¿VizIR - A Framework for Visual Information Retrieval¿, submitted by the Institute of Software Technology and Interactive Systems at the Vienna University of Technology, aims at three major goals: (1) Integration of past visual information retrieval research results with our current research work on similarity modeling, (semantic) feature extraction and query acceleration. We have developed a process-oriented similarity model that is based on psychological insights about human similarity perception as well as information retrieval methods. The major idea is that visual similarity is more than distance measurement of numerical feature vectors. In feature design we have developed a concept for semantic feature modeling. Additionally, we are integrating and evaluating the visual MPEG-7 descriptors and developing suitable descriptor schemes for visual querying. (2) Implementation of an asset framework for content-based retrieval of visual media (image, video). Assets include class frameworks for feature extraction, querying methods and user interface components as well as benchmarking algorithms, test sets and documentation. This asset framework has to be open, portable, extendible and well-documented. Open means that the VizIR outcome (including source-code and API documentation) will be regularly released to the public and interested researchers are invited (in publications, etc.) to use this toolbox. VizIR is portable, because it is fully based on Java and the JavaSDK. Where platform-dependent packages are used (database, media handling), they are encapsulated in wrapper classes to guarantee that these components can be replaced without having to change the framework API. VizIR is designed to be extendible: users can add feature extraction methods, query engines, indexing methods, user interface components, etc. Finally, well-documented APIs and components are guaranteed through using Javadoc and state-of-the-art software development processes and tools. (3) Cooperation with other visual information retrieval research groups. In VizIR, we are using innovations from other groups like the Multimedia Retrieval Markup Language, test sets, etc. and contributing to other project (e.g. Benchathlon, an initiative to design benchmarks for visual information retrieval). The VizIR project has already been started in Autumn 2001. With funding from the FWF we hope to accelerate project progress and maximize the scientific output.

Funding provided by

  • FWF - Österr. Wissenschaftsfonds