Unconstrained face recognition using MRF priors and manifold traversing

Ricardo N. Rodrigues, Greyce N. Schroeder, Jason J. Corso, Venu Govindaraju

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper, we explore new methods to improve the modeling of facial images under different types of variations like pose, ambient illumination and facial expression. We investigate the intuitive assumption that the parameters for the distribution of facial images change smoothly with respect to variations in the face pose angle. A Markov Random Field is defined to model a smooth prior over the parameter space and the maximum a posteriori solution is computed. We also propose extensions to the view-based face recognition method by learning how to traverse between different subspaces so we can synthesize facial images with different characteristics for the same person. This allow us to enroll a new user with a single 2D image.

Original languageEnglish
Title of host publicationIEEE 3rd International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems, BTAS 2009
DOIs
StatePublished - 2009
EventIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009 - Washington, DC, United States
Duration: 28 Sep 200930 Sep 2009

Publication series

NameIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009

Conference

ConferenceIEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
Country/TerritoryUnited States
CityWashington, DC
Period28/09/0930/09/09

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