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Surface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras
Aouada, Djamila; Al Ismaeil, Kassem; Kedir Idris, Kedija et al.
2014In 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14)
Peer reviewed
 

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Keywords :
Face recognition; Super resolution; Depth data
Abstract :
[en] We address the limitation of low resolution depth cameras in the context of face recognition. Considering a face as a surface in 3-D, we reformulate the recently proposed Upsampling for Precise Super–Resolution algorithm as a new approach on three dimensional points. This reformulation allows an efficient implementation, and leads to a largely enhanced 3-D face reconstruction. Moreover, combined with a dedicated face detection and representation pipeline, the proposed method provides an improved face recognition system using low resolution depth cameras. We show experimentally that this system increases the face recognition rate as compared to directly using the low resolution raw data.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust
Disciplines :
Electrical & electronics engineering
Author, co-author :
Aouada, Djamila  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Al Ismaeil, Kassem ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Kedir Idris, Kedija
Ottersten, Björn ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Surface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras
Publication date :
2014
Event name :
11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)
Event date :
26-08-2014 to 29-08-2014
Audience :
International
Main work title :
11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14)
Peer reviewed :
Peer reviewed
Name of the research project :
R-AGR-0686-1 > C11/IS/1204105 : FAVE > 01/01/2012 - 31/12/2014 > OTTERSTEN Björn
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
since 24 June 2014

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