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.
Description
@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}
}