Person Re-Identification from Depth Cameras using Skeleton and 3D Face Data

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dc.contributor.authorPala, Pietroen_US
dc.contributor.authorSeidenari, Lorenzoen_US
dc.contributor.authorBerretti, Stefanoen_US
dc.contributor.authorBimbo, Alberto Delen_US
dc.contributor.editorTelea, Alex and Theoharis, Theoharis and Veltkamp, Remcoen_US
dc.date.accessioned2018-04-14T18:28:43Z
dc.date.available2018-04-14T18:28:43Z
dc.date.issued2018
dc.description.abstractIn the typical approach, person re-identification is performed using appearance in 2D still images or videos, thus invalidating any application in which a person may change dress across subsequent acquisitions. For example, this is a relevant scenario for home patient monitoring. Depth cameras enable person re-identification exploiting 3D information that captures biometric cues such as face and characteristic dimensions of the body. Unfortunately, face and skeleton quality is not always enough to grant a correct recognition from depth data. Both features are affected by the pose of the subject and the distance from the camera. In this paper, we propose a model to incorporate a robust skeleton representation with a highly discriminative face feature, weighting samples by their quality. Our method combining face and skeleton data improves rank-1 accuracy compared to individual cues especially on short realistic sequences.en_US
dc.description.sectionheadersPapers II
dc.description.seriesinformationEurographics Workshop on 3D Object Retrieval
dc.identifier.doi10.2312/3dor.20181058
dc.identifier.isbn978-3-03868-053-6
dc.identifier.issn1997-0471
dc.identifier.pages95-101
dc.identifier.urihttps://doi.org/10.2312/3dor.20181058
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/3dor20181058
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectBiometrics
dc.subjectComputer vision representations
dc.subject3D imaging
dc.titlePerson Re-Identification from Depth Cameras using Skeleton and 3D Face Dataen_US
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