Learning a model of facial shape and expression from 4D scans - - PowerPoint PPT Presentation

learning a model of facial shape and expression from 4d
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Learning a model of facial shape and expression from 4D scans - - PowerPoint PPT Presentation

Learning a model of facial shape and expression from 4D scans Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, Javier Romero SIGGRAPH Asia 2017 Note: this slide is a static .pdf version (no video) For video, please see:


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Learning a model of facial shape and expression from 4D scans

Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, Javier Romero SIGGRAPH Asia 2017

Note: this slide is a static .pdf version (no video) For video, please see: https://youtu.be/36rPTkhiJTM

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SLIDE 2

Realistic Virtual Character

Warner Bros. & Paramount Pictures

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Realistic Virtual Character

Warner Bros. & Paramount Pictures

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Consumer Application

Apple 2017

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Spectrum of Face Models

“Low-end” “High-end”

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Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes

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SLIDE 7

Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes Blanz and Vetter 1999 & Basel Face Model [Paysan et al. 2009]

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SLIDE 8

Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes Blanz and Vetter 1999 FaceWarehouse [Cao et al. 2014] & Basel Face Model [Paysan et al. 2009]

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SLIDE 9

Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes Blanz and Vetter 1999 FaceWarehouse [Cao et al. 2014] Wu et al. 2016 & Basel Face Model [Paysan et al. 2009]

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SLIDE 10

Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes Blanz and Vetter 1999 FaceWarehouse [Cao et al. 2014] Wu et al. 2016 Digital Emily [Alexander et al. 2009] & Basel Face Model [Paysan et al. 2009]

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SLIDE 11

Spectrum of Face Models

“Low-end” “High-end”

FACS-based blendshapes Blanz and Vetter 1999 FaceWarehouse [Cao et al. 2014] Wu et al. 2016 Digital Emily [Alexander et al. 2009] & Basel Face Model [Paysan et al. 2009]

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FLAME Face Model

Issues FLAME

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FLAME Face Model

Limited identity coverage Learned from ~4000 identities Issues FLAME

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FLAME Face Model

Limited identity coverage Learned from ~4000 identities Issues FLAME Artist designed expression Learned from high-quality 4D expression scans

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FLAME Face Model

Limited identity coverage Learned from ~4000 identities Issues FLAME Artist designed expression Learned from high-quality 4D expression scans Over-complete FACS basis Orthogonal expression space

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FLAME Face Model

Limited identity coverage Learned from ~4000 identities Issues FLAME Artist designed expression Learned from high-quality 4D expression scans Over-complete FACS basis Orthogonal expression space Non-linearity of jaw and neck Modeled as rotatable joints Activated by linear blend skinning Pose blendshapes further capture details

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FLAME Face Model

Limited identity coverage Learned from ~4000 identities Issues FLAME Artist designed expression Learned from high-quality 4D expression scans Over-complete FACS basis Orthogonal expression space Non-linearity of jaw and neck Modeled as rotatable joints Activated by linear blend skinning Pose blendshapes further capture details Require artist work Fully automatic registration and modeling

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FLAME Face Model

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FLAME Face Model

Template

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FLAME Face Model

Template Shape

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FLAME Face Model

Template Shape Shape +Pose

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FLAME Face Model

Template Shape Shape + Pose + Expression Shape +Pose

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Overview

Co-registration Hirshberg et al. 12

CAESAR dataset Shape Data Registration Shape Model Training MPI FacialMotion dataset Pose Data Registration Pose Model Training Expression Data Registration Expression Model Training D3DFACS dataset Initial Expression Blendshapes

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Overview

Co-registration Hirshberg et al. 12

CAESAR dataset Shape Data Registration Shape Model Training MPI FacialMotion dataset Pose Data Registration Pose Model Training Expression Data Registration Expression Model Training D3DFACS dataset Initial Expression Blendshapes

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Shape Model

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Shape Data

Registration of CAESAR datasets [Robinette et al. 2002]

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Learned Shape Model

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Pose Model

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Pose Data

Registration of MPI FacialMotion datasets for pose training

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Learned Pose Model

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Effect of Pose Blendshapes

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Expression Model

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Expression Data

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Expression Data

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4D Scans into Correspondence

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Coarse-to-Fine Registration

>1 mm 0 mm

Stage 1: model-only

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Coarse-to-Fine Registration

>1 mm 0 mm

Stage2: coupled

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Coarse-to-Fine Registration

>1 mm 0 mm

Stage 3: Texture-based Alignment

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Effect of Texture-based Alignment

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Effect of Texture-based Alignment

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Registration Results

>1 mm 0 mm

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Registration Results

>1 mm 0 mm

Detail expressions such as eye blinking are also captured

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Learned Expression Model

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Results

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Compare on Identity Space

FaceWarehouse [Cao et al. 2014] 50 components FLAME 49 49 components + 1 for gender

0 mm >1 mm

BU-3DFE scan Fitting Scan-to-Mesh Distance Fitting Scan-to-Mesh Distance

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Compare on Identity Space

FLAME 198 198 components + 1 for gender

0 mm >1 mm

BU-3DFE scan Fitting Scan-to-Mesh Distance Fitting Scan-to-Mesh Distance Basel Face Model (BFM) [Paysan et al. 2009] 199 components

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SLIDE 47

Compare on Identity Space

FLAME 198 198 components + 1 for gender

0 mm >1 mm

BU-3DFE scan Scan-to-Mesh Distance Scan-to-Mesh Distance Basel Face Model (BFM) 199 components BU-3DFE scan

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SLIDE 48

Compare on Identity Space

0.5 1 1.5 2

Error [mm]

20 40 60 80 100

Percentage

FLAME 300 FLAME 198 FLAME 90 FLAME 49 FW BFM Full BFM 91 BFM 50

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SLIDE 49

Compare on Identity Space

FW 50: 67% BFM 50: 69% FLAME 49: 74% BFM 199: 92% FLAME 198: 94% FLAME 300: 96%

FLAME: our model BFM: Basel Face Model FW FaceWarehouse Note: higher value is better

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Compare on Expression Space

>3 mm 0 mm

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Sparse Landmark Fitting

FLAME produces better result in 2D landmark fitting

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Application: Retargeting

FLAME retargeting pipeline

FLAME Face Model

Source Retargeted

Target Scan Expression & pose Identity

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Application: Retargeting

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Conclusion

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What did we learn

  • Large high-quality data
  • Separation of identity, pose and expression
  • Importance of face prior
  • Model and data available for research purpose
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Future Work

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Acknowledgement

Tsvetelina Alexiadis, Andrea Keller, Jorge Márquez Data Acquisition Shunsuke Saito & Cassidy Laidlaw Evaluation Yinghao Huang, Ahmed Osman, Naureen Mahmood Discussion Talha Zaman Video Recording Alejandra Quiros-Ramirez Project Website Darren Cosker Advice and D3DFACS Dataset

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SLIDE 58

Thank You! http://flame.is.tue.mpg.de/

Registrations for D3DFACS dataset FLAME face model (male / female) with example code