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

Pala, Pietro; Seidenari, Lorenzo; Berretti, Stefano; Bimbo, Alberto Del

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

Files

095-101.pdf (5.32 MB)

Date

2018

Authors

Pala, Pietro
Seidenari, Lorenzo
Berretti, Stefano
Bimbo, Alberto Del

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.

        @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
}
}