Reference : Real-Time Non-Rigid Multi-Frame Depth Video Super-Resolution

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/21434

Title :	Real-Time Non-Rigid Multi-Frame Depth Video Super-Resolution
Language :	English
Author, co-author :	Al Ismaeil, Kassem [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Aouada, Djamila [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Solignac, Thomas []
	Mirbach, Bruno []
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	12-Jun-2015
Main document title :	IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'15), (Best paper award)
Peer reviewed :	Yes
Audience :	International
Event name :	IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), (Best paper award)
Event date :	07-06-2015 to 12-06-2015
Keywords :	[en] Real-Time ; Non-Rigid Depth Video ; Multi-Frame Super Resolution
Abstract :	[en] This paper proposes to enhance low resolution dynamic depth videos containing freely non–rigidly moving objects with a new dynamic multi–frame super–resolution algorithm. Existent methods are either limited to rigid objects, or restricted to global lateral motions discarding radial displacements. We address these shortcomings by accounting for non–rigid displacements in 3D. In addition to 2D optical flow, we estimate the depth displacement, and simultaneously correct the depth measurement by Kalman filtering. This concept is incorporated efficiently in a multi–frame super–resolution framework. It is formulated in a recursive manner that ensures an efficient deployment in real–time. Results show the overall improved performance of the proposed method as compared to alternative approaches, and specifically in handling relatively large 3D motions. Test examples range from a full moving human body to a highly dynamic facial video with varying expressions.
Research centres :	SnT, Interdisciplinary Centre for Security, Reliability and Trust
Name of the research project :	I2R-DIR-PFN-11FAVE > C11/IS/1204105 : FAVE > 01/01/2012 - 31/12/2014 > OTTERSTEN Björn
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/21434

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access CVPR2015_MSF_Camera Ready (2).pdf Author preprint 5.93 MB View/Open

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