Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Other Grants and Activities

International Projects

FP6 European Project CLASS

Participants : Moray Allan, Matthieu Guillaumin, Alexander Kläser, Thomas Mensink, Cordelia Schmid, Jakob Verbeek.

CLASS (Cognitive-Level Annotation using latent Statistical Structure) is a 6th framework Cognitive Systems STREP that started in January 2006 for three and half years. It is a basic research project focused on developing a specific cognitive ability for use in intelligent content analysis: the automatic discovery of content categories and attributes from unstructured content streams. It studies both fully autonomous and semi-supervised methods. The work combines robust computer vision based image descriptors, machine learning based latent structure models, and advanced textual summarization techniques. The potential applications of the basic research results are illustrated by three demonstrators: an image interrogator that interactively answers simple user-defined queries about image content; an automatic annotator for people and actions in situation comedy videos; an automatic news story summarizer. The Class consortium is interdisciplinary, combining leading European research teams in visual recognition, text understanding and summarization, and machine learning: LEAR; LJK; Oxford University, UK; K.U. Leuven, Belgium; University of Helsinki, Finland; and MPI Tuebingen, Germany.

FP7 European Network of Excellence PASCAL 2

Participants : Adrien Gaidon, Matthieu Guillaumin, Frédéric Jurie, Cordelia Schmid, Jakob Verbeek.

PASCAL (Pattern Analysis, Statistical Modeling and Computational Learning) is a 7th framework EU Network of Excellence that started in March 2008 for five years. It has established a distributed institute that brings together researchers and students across Europe, and is now reaching out to countries all over the world. PASCAL is developing the expertise and scientific results that will help create new technologies such as intelligent interfaces and adaptive cognitive systems. To achieve this, it supports and encourages collaboration between experts in machine learning, statistics and optimization. It also promotes the use of machine learning in many relevant application domains such as machine vision.


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