2D and 3D face localization for complex scenes

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dc.contributor.author Karame, G en
dc.contributor.author Stergiou, A en
dc.contributor.author Katsarakis, N en
dc.contributor.author Papageorgiou, P en
dc.contributor.author Pnevmatikakis, A en
dc.date.accessioned 2014-03-01T02:51:00Z
dc.date.available 2014-03-01T02:51:00Z
dc.date.issued 2007 en
dc.identifier.uri http://hdl.handle.net/123456789/35288
dc.subject.other Cameras en
dc.subject.other Computer networks en
dc.subject.other Face recognition en
dc.subject.other Stochastic models en
dc.subject.other Stochastic programming en
dc.subject.other Three dimensional en
dc.subject.other (algorithmic) complexity en
dc.subject.other 3D faces en
dc.subject.other 3D scenes en
dc.subject.other camera view en
dc.subject.other Complex scenes en
dc.subject.other Existing systems en
dc.subject.other Face localization en
dc.subject.other Face tracking en
dc.subject.other far fields en
dc.subject.other Gaussian mixture model (GMM) en
dc.subject.other Multiple people en
dc.subject.other Security systems en
dc.title 2D and 3D face localization for complex scenes en
heal.type conferenceItem en
heal.identifier.primary 10.1109/AVSS.2007.4425339 en
heal.identifier.secondary http://dx.doi.org/10.1109/AVSS.2007.4425339 en
heal.identifier.secondary 4425339 en
heal.publicationDate 2007 en
heal.abstract In this paper, we address face tracking of multiple people in complex 3D scenes, using multiple calibrated and synchronized far-field recordings. We localize faces in every camera view and associate them across the different views. To cope with the complexity of 2D face localization introduced by the multitude of people and unconstrained face poses, a combination of stochastic and deterministic trackers, detectors and a Gaussian Mixture Model for face validation are utilized. Then faces of the same person seen from the different cameras are associated by first finding all possible associations and then choosing the best option by means of a 3D stochastic tracker. The performance of the proposed system is evaluated and is found enhanced compared to existing systems. © 2007 IEEE. en
heal.journalName 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007 Proceedings en
dc.identifier.doi 10.1109/AVSS.2007.4425339 en
dc.identifier.spage 371 en
dc.identifier.epage 376 en

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