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Conference papers
Benchmarking asymmetric 3D-2D face recognition systems
Abstract : — Asymmetric 3D-2D face recognition (FR) aims to
recognize individuals from 2D face images using textured 3D
face models in the gallery (or vice versa). This new FR scenario
has the potential to be readily deployable in field applications
while still keeping the advantages of 3D FR solutions of being
more robust to pose and lighting variations. In this paper, we
propose a new experimental protocol based on the UHDB11
dataset for benchmarking 3D-2D FR algorithms. This new
experimental protocol allows for the study of the performance
of a 3D-2D FR solution under pose and/or lighting variations.
Furthermore, we also benchmarked two state of the art 3D-
2D FR algorithms. One is based on the Annotated Deformable
Model (using manually labeled landmarks in this paper) using
manually labeled landmarks whereas the other makes use
of Oriented Gradient Maps along with an automatic pose
estimation through random forest.
https://hal.archives-ouvertes.fr/hal-01339319
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, June 29, 2016 - 3:52:44 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:45 PM
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, June 29, 2016 - 3:52:44 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:45 PM