Objetivo 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. Ámbito científico 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 Programa(s) 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 Tema(s) MSCA-IF-2014-GF - Marie Skłodowska-Curie Individual Fellowships (IF-GF) Convocatoria de propuestas H2020-MSCA-IF-2014 Consulte otros proyectos de esta convocatoria Régimen de financiación MSCA-IF-GF - Global Fellowships Coordinador PANEPISTIMIO IOANNINON Aportación neta de la UEn € 168 391,80 Dirección PANEPISTEMIOYPOLE PANEPISTEMIO IOANNINON 45110 Ioannina Grecia Ver en el mapa Región Βόρεια Ελλάδα Ήπειρος Ιωάννινα Tipo de actividad Higher or Secondary Education Establishments Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Coste total € 168 391,80 Socios (1) Ordenar alfabéticamente Ordenar por aportación neta de la UE Ampliar todo Contraer todo Socio Las organizaciones asociadas contribuyen a la aplicación de la acción, pero no firman el acuerdo de subvención. UNIVERSITY OF HOUSTON SYSTEM Estados Unidos Aportación neta de la UEn € 0,00 Dirección EZEKIEL CULLEN BUILDING 203 772042022 Houston Ver en el mapa Tipo de actividad Higher or Secondary Education Establishments Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Coste total € 86 065,20