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

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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In 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.
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@inproceedings{
10.2312:3dor.20181058
, booktitle = {
Eurographics Workshop on 3D Object Retrieval
}, editor = {
Telea, Alex and Theoharis, Theoharis and Veltkamp, Remco
}, title = {{
Person Re-Identification from Depth Cameras using Skeleton and 3D Face Data
}}, author = {
Pala, Pietro
and
Seidenari, Lorenzo
and
Berretti, Stefano
and
Bimbo, Alberto Del
}, year = {
2018
}, publisher = {
The Eurographics Association
}, ISSN = {
1997-0471
}, ISBN = {
978-3-03868-053-6
}, DOI = {
10.2312/3dor.20181058
} }
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