3D head pose estimation and tracking using particle filtering and ICP algorithm

Handle URI:
http://hdl.handle.net/10754/564256
Title:
3D head pose estimation and tracking using particle filtering and ICP algorithm
Authors:
Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge
Abstract:
This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.
KAUST Department:
Electrical Engineering Program
Publisher:
Springer Science + Business Media
Journal:
Articulated Motion and Deformable Objects
Conference/Event name:
6th International Conference on Articulated Motion and Deformable Objects, AMDO 2010
Issue Date:
2010
DOI:
10.1007/978-3-642-14061-7_22
Type:
Conference Paper
ISSN:
03029743
ISBN:
3642140602; 9783642140600
Appears in Collections:
Conference Papers; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorBen Ghorbel, Mahdien
dc.contributor.authorBaklouti, Maleken
dc.contributor.authorCouvet, Sergeen
dc.date.accessioned2015-08-04T06:20:54Zen
dc.date.available2015-08-04T06:20:54Zen
dc.date.issued2010en
dc.identifier.isbn3642140602; 9783642140600en
dc.identifier.issn03029743en
dc.identifier.doi10.1007/978-3-642-14061-7_22en
dc.identifier.urihttp://hdl.handle.net/10754/564256en
dc.description.abstractThis paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.en
dc.publisherSpringer Science + Business Mediaen
dc.title3D head pose estimation and tracking using particle filtering and ICP algorithmen
dc.typeConference Paperen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalArticulated Motion and Deformable Objectsen
dc.conference.date7 July 2010 through 9 July 2010en
dc.conference.name6th International Conference on Articulated Motion and Deformable Objects, AMDO 2010en
dc.conference.locationPort d'Andratx, Mallorcaen
kaust.authorBen Ghorbel, Mahdien
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