Obiettivo 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. Campo scientifico natural sciencescomputer and information sciencesdatabasesnatural scienceschemical sciencesinorganic chemistrytransition metalsnatural sciencescomputer and information sciencesartificial intelligencecomputer visionnatural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencescomputer and information sciencesartificial intelligencepattern recognition Programma(i) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Argomento(i) MSCA-IF-2014-GF - Marie Skłodowska-Curie Individual Fellowships (IF-GF) Invito a presentare proposte H2020-MSCA-IF-2014 Vedi altri progetti per questo bando Meccanismo di finanziamento MSCA-IF-GF - Global Fellowships Coordinatore PANEPISTIMIO IOANNINON Contribution nette de l'UE € 168 391,80 Indirizzo PANEPISTEMIOYPOLE PANEPISTEMIO IOANNINON 45110 Ioannina Grecia Mostra sulla mappa Regione Βόρεια Ελλάδα Ήπειρος Ιωάννινα Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 168 391,80 Partner (1) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto Partner Le organizzazioni partner contribuiscono all’attuazione dell’azione, ma non sottoscrivono l’accordo di sovvenzione. UNIVERSITY OF HOUSTON SYSTEM Stati Uniti Contribution nette de l'UE € 0,00 Indirizzo EZEKIEL CULLEN BUILDING 203 772042022 Houston Mostra sulla mappa Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 86 065,20