Reference : Surface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/17040

Title :	Surface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras
Language :	English
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) > >]
Publication date :	2014
Main document title :	11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14)
Peer reviewed :	Yes
Audience :	International
Event name :	11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)
Event date :	26-08-2014 to 29-08-2014
Keywords :	[en] 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 centres :	Interdisciplinary Centre for Security, Reliability and Trust
Funders :	Fonds National de la Recherche - FnR
Name of the research project :	I2R-DIR-PFN-11FAVE > C11/IS/1204105 : FAVE > 01/01/2012 - 31/12/2014 > OTTERSTEN Björn
Permalink :	http://hdl.handle.net/10993/17040

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