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Learning Texture Descriptors

Objective

We aim to develop novel computational models for describing image textures. By image textures, we mean patterns which arise when many similar structures co-occur. Humans find no difficulties in recognizing thousands of different textures, whether they are natural (grass, sand, sea waves) or artificial (textiles, manufactured surface finishes). The basic goal of this project is to develop novel algorithms for learning texture representations from images. The desiderata for the outcome are good performance (ability to successfully recognize and synthesize textures), scalability (efficient, sub-linear representation and recognition of increasing number of textures) and effectiveness (learning new patterns from small number of examples). As an integral part of the project, we also aim to design benchmarking standards which would enable us, and the computer vision community, to evaluate and compare different texture descriptors.

Field of science

  • /natural sciences/computer and information sciences/artificial intelligence/computer vision

Call for proposal

FP7-PEOPLE-ERG-2008
See other projects for this call

Funding Scheme

MC-ERG - European Re-integration Grants (ERG)
Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Coordinator

CESKE VYSOKE UCENI TECHNICKE V PRAZE
Address
Jugoslavskych Partyzanu 1580/3
160 00 Praha
Czechia
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 45 000
Administrative Contact
Igor Mraz (Mr.)