LEARNTEX

Learning Texture Descriptors

 Coordinatore CESKE VYSOKE UCENI TECHNICKE V PRAZE 

 Organization address address: ZIKOVA 4
city: PRAHA
postcode: 166 36

contact info
Titolo: Mr.
Nome: Igor
Cognome: Mraz
Email: send email
Telefono: 420224000000
Fax: 420224000000

 Nazionalità Coordinatore Czech Republic [CZ]
 Totale costo 45˙000 €
 EC contributo 45˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-ERG-2008
 Funding Scheme MC-ERG
 Anno di inizio 2009
 Periodo (anno-mese-giorno) 2009-01-01   -   2011-12-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    CESKE VYSOKE UCENI TECHNICKE V PRAZE

 Organization address address: ZIKOVA 4
city: PRAHA
postcode: 166 36

contact info
Titolo: Mr.
Nome: Igor
Cognome: Mraz
Email: send email
Telefono: 420224000000
Fax: 420224000000

CZ (PRAHA) coordinator 0.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

patterns    learning    image    textures    texture   

 Obiettivo del progetto (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.'

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