Face Face Identification Identification by by Fitting Fitting a a 3D 3D Morphable Model Morphable Model using using Linear Linear Shape and Texture Shape and Texture Error Functions Error Functions Sami Romdhani Volker Blanz Thomas Vetter University of Freiburg Supported by DARPA
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Sami Romdhani Volker Blanz Thomas Vetter University of Freiburg Supported by DARPA
Face Identification by Fitting a 3D Morphable Model using Linear Shape and Texture Error Functions. Sami Romdhani Volker Blanz Thomas Vetter University of Freiburg Supported by DARPA. The Problem. Historical Methods 3D Morphable Model LiST : a Novel Fitting Algorithm - PowerPoint PPT Presentation
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Face Face IdentificationIdentificationby by FittingFitting a a
3D3D Morphable Model Morphable Modelusing using LinearLinear Shape and Texture Error Shape and Texture Error
FunctionsFunctions
Sami Romdhani Volker Blanz Thomas Vetter
University of Freiburg
Supported by DARPA
7th ECCV – 31 May 2002 - Volume 4, pp 3 - 19 2/26
The ProblemThe Problem
7th ECCV – 31 May 2002 - Volume 4, pp 3 - 19 3/26
MenuMenu
Historical Methods
3D Morphable Model
LiST : a Novel Fitting Algorithm
Identification Experiments on more than 5000 Images
Identification Confidence = Fitting Accuracy
7th ECCV – 31 May 2002 - Volume 4, pp 3 - 19 4/26
Historical Methods : Historical Methods : Active Appearance ModelActive Appearance Model
Use of a generative model:
1. View based (2D), Correspondence basedex: AAM of Cootes and Taylor
Novel Fitting Algorithm :• Use of Optical Flow to recover a Shape Error• Recovers most of the parameters linearly• Recovers a few non-linear parameters using
Lev.-Mar.
State of the art identification performances across
Pose & Illumination
Drawbacks:• Still not fast enough• Still requires manual initialisation