Powered by OpenAIRE graph
View all 10 versions

University of Ioannina

corporate_fareorganization
Web page: http://www.uoi.gr/en/
Country: Greece

ROR: https://ror.org/01qg3j183

Wikidata: Q1229924

ISNI: 0000000121087481

FundRef: 501100021855

University of Ioannina

Funder
Top 100 values are shown in the filters
Results number
arrow_drop_down
143 Projects, page 1 of 29

  • MICROBEGR (Supporting environmental microbiology and biotechnology research potential in Western Greece)

    assignment_turned_inProject2008 - 2011Partners:University of Ioannina
    Funder: European Commission Project Code: 203590
    more_vert

  • StillNoFace (Identity matching from still images without face information)

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Open Access Mandate for Publications assignment_turned_inProject2015 - 2017Partners:University of Ioannina
    Funder: European Commission Project Code: 656094
    Overall Budget: 168,392 EURFunder Contribution: 168,392 EUR

    In computer vision, human identity matching from images and/or video has been an active research topic for more than two decades and its popularity is increasing with the increase in computing power. The state of the art techniques are based on face images and gait recognition from long video sequences. However, in many real applications only some static images of the subject may be available where face information is missing (e.g. posterior views). These scenarios have not been addressed by the research community as they are difficult to handle. In this action, we propose a method for matching identities from a set of 2D images of a person without any facial information. The method consists of two steps: at first, the human body is modelled by a 3D articulated model whose pose is estimated by its 2D projections onto the images. Then, biometric features are computed by fitting 3D deformable models to the image data, thus capturing the form and size of the main parts of the anatomy. The overall framework works under a probabilistic framework, with a learning step, in order to encode pose and anatomy variations between a set of individuals that are to be identified.

    more_vert

  • LOMAIVITICINS (THE SYNTHESIS OF DIAZOBENZOFLUORENE ANTITUMOR ANTIBIOTICS: LOMAIVITICINS A, B AND KINAMYCIN C)

    assignment_turned_inProject2008 - 2012Partners:University of Ioannina
    Funder: European Commission Project Code: 200176
    more_vert

  • JMUGCS (Jointly Mining User Generated Content Sources)

    assignment_turned_inProject2012 - 2016Partners:University of Ioannina
    Funder: European Commission Project Code: 322375
    more_vert

  • CLOVISEN (Cross-Layer Optimization for Visual Sensor Networks)

    assignment_turned_inProject2009 - 2013Partners:University of Ioannina
    Funder: European Commission Project Code: 239195
    more_vert
  • chevron_left
  • 1
  • 2
  • 3
  • 4
  • 5
  • chevron_right

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

Content report
No reports available
Funder report
No option selected
arrow_drop_down

Do you wish to download a CSV file? Note that this process may take a while.

There was an error in csv downloading. Please try again later.