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EU NOBLESSE ESPRIT




Nonlinear Model-Based Analysis and Description of Images for Multimedia Applications (NOBLESSE)

Project Members

  • Prof. Burkhardt   (project leader)
  • Prof. Dr. M. Gabbouj, Tampere University of Technology
  • Prof. Dr. M. Kunt, Swiss Federal Institute of Technology Lausanne
  • Dr. S. Marshall, University of Strathclyde Glasgow
  • Prof. Dr. I. Pitas, Aristotle University of Thessaloniki
  • Prof. Dr. G. Ramponi, University of Trieste
  • Prof. Dr. J. Serra, Prof. Dr. F. Meyer, Ecole des Mines de Paris

Introduction

The objective of the project is to develop especially new nonlinear model-based descriptions of images and image sequences and thus a dense parametric description.

Approach

The objective of the project is to develop especially new nonlinear model-based descriptions of images and image sequences and thus a dense parametric description. The large amount of image-data in multimedia applications makes it necessary to code the information in a model-based symbolic form. A high measure of compactness in the data representation can be foreseen if the power of nonlinear models is taken into account. Beside the potential for image coding purposes a high-level description is an absolute prerequisite to support the application of higher level functions like model-based browsing and navigation, keying, image sequence interpolation, tracking and finding salient regions, querying (similarity measures, indexing, fuzzy similarity measures).

To meet the challenging tasks in multimedia applications there is a need for new sophisticated model-based schemes for a high-level description of images and image sequences. We expect novel results opening new potential fields of application like the support for building databases in multimedia applications, image archiving and image sequence coding. There are a plethora of applications that can make heavy use of these representations in a multimedia context, for example, for browsing in a large database with minimum search time. A new application is to use automatic segmentation techniques for the isolation of commercials in image sequences and substitute them with others for different countries (automatic cutting and pasting).

A high measure of compactness in the data representation can be foreseen if the potential of nonlinear models is taken into account like:

polynomial models, motion models, Markov models, set-based models (rank-order, morphological, region growing like watershed etc.), stochastic and chaotic models, genetic algorithms and fuzzy models, canonical frames with invariants, 3D models, models for interpolation.

The methods must be applied to still images as well as to image sequences. Another point of interest is data fusion in multimedia applications, i.e. to combine features in different representations (e.g. audio and video) to increase the database for searching and classification.

Current models were mainly developed for image coding purposes. They are rather simple and far away from being optimal and do not contribute to more complex tasks like those needed in image databases. The research will focus on standard video sequences; however, more advanced tasks for future standards like stereo pairs and 3D images (virtual reality) will also be investigated.

References

  1. newsletter_1.ps (October 1996)
  2. newsletter_2.ps (April 1997)
  3. newsletter_3.ps (October 1997)
  4. newsletter_4.ps (June 1998)
  5. newsletter_5.ps (December 1998)

Publications and Events

Workshop: Nonlinear Methods in Model-Based Image Interpretation

  • date: Sept 20, 1996 (directly after ICIP96)
  • place: Lausanne/Switzerland

Industrial Day

  • date: Sept 1/2, 1997
  • place: Freiburg/Germany
  • Further information (programme, registration etc.) can be found here

European Course on Recent Advances in Image Processing

  • date: March 2-6, 1998
  • place: Trieste/Italy

NOBLESSE Workshop on Non-Linear Model Based Image Analysis (NMBIA ´98)

  • date: July 1-3, 1998
  • place: Glasgow/Scotland

  1. [bu:sig:noblessebook2000] H. Burkhardt and S. Siggelkow.
    Invariant features in pattern recognition - fundamentals and applications.
    In C. Kotropoulos and I. Pitas, editors, Nonlinear Model-Based Image/Video Processing and Analysis, pages 269-307. John Wiley & Sons, 2001.