Human Face Reconstruction Using Bayesian Deformable Models

Mamic, George J., Fookes, Clinton B., & Sridharan, Sridha (2006) Human Face Reconstruction Using Bayesian Deformable Models. In IEEE International Conference on Video and Signal Based Surveillance, 2006. AVSS '06, 22-24 November 2006, Sydney, NSW.

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Abstract

This paper presents a Bayesian framework for 3D facial reconstruction. The framework iteratively deforms a generic face mesh to fit a set of range points representing a face. The generic mesh is generated from the extensive FRGC database of face images. The deformation process is conducted within a Bayesian framework and is driven by a Markov Chain Monte Carlo (MCMC) sampler which uses information from the likelihood and prior distributions of the generic face mesh. The paper presents results on the construction of a generic face model, the deformation framework and fitting results to both synthetic and real data. The results verify the effectiveness of the proposed technique, accurately deforming a generic face mesh to captured 3D data points of human faces.

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ID Code: 9407
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1109/AVSS.2006.60
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2006 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 10 Sep 2007 00:00
Last Modified: 29 Feb 2012 13:22

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