Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

Handle URI:
http://hdl.handle.net/10754/564435
Title:
Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities
Authors:
Li, Huibin; Huang, Di; Lemaire, Pierre; Morvan, Jean-Marie; Chen, Liming
Abstract:
This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.
KAUST Department:
Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2011 18th IEEE International Conference on Image Processing
Conference/Event name:
2011 18th IEEE International Conference on Image Processing, ICIP 2011
Issue Date:
Sep-2011
DOI:
10.1109/ICIP.2011.6116308
Type:
Conference Paper
ISSN:
15224880
ISBN:
9781457713033
Appears in Collections:
Conference Papers; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Huibinen
dc.contributor.authorHuang, Dien
dc.contributor.authorLemaire, Pierreen
dc.contributor.authorMorvan, Jean-Marieen
dc.contributor.authorChen, Limingen
dc.date.accessioned2015-08-04T07:00:52Zen
dc.date.available2015-08-04T07:00:52Zen
dc.date.issued2011-09en
dc.identifier.isbn9781457713033en
dc.identifier.issn15224880en
dc.identifier.doi10.1109/ICIP.2011.6116308en
dc.identifier.urihttp://hdl.handle.net/10754/564435en
dc.description.abstractThis paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subject3D shape descriptoren
dc.subjecthistograms of multiple order surface differential quantitiesen
dc.subjectmesh-based 3D face recognitionen
dc.titleExpression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantitiesen
dc.typeConference Paperen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2011 18th IEEE International Conference on Image Processingen
dc.conference.date11 September 2011 through 14 September 2011en
dc.conference.name2011 18th IEEE International Conference on Image Processing, ICIP 2011en
dc.conference.locationBrusselsen
dc.contributor.institutionUniversité de Lyon, CNRS, F-69134, Lyon, Franceen
dc.contributor.institutionEcole Centrale de Lyon, LIRIS UMR5205, F-69134, Lyon, Franceen
dc.contributor.institutionUniversité Lyon 1, Institut Camille Jordan, 43 blvd. du 11 Nov. 1918, F-69622 Villeurbanne - Cedex, Franceen
kaust.authorMorvan, Jean-Marieen
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