exploring the space of human body shapes: data-driven synthesis under anthropometric control brett...

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Exploring the space of human body shapes: data-driven synthesis under anthropometric control Brett Allen Brian Curless Zoran Popović University of Washington 2004-01-2188

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Exploring the space of human body shapes:

data-driven synthesisunder anthropometric control

Brett AllenBrian CurlessZoran Popović

University of Washington

2004-01-2188

MotivationTraditional anthropometry has focused on

sets ofone-dimensional measurements.

MotivationFull body shape capture promises to advance

the state of the art.

?

CAESARCivilian American & European Surface Anthropometry Resource

• thousands of subjects in the U.S. and Europe• traditional anthropometry• demographic survey• laser range scans

We’ll use 250 of these scans (125 male, 125 female).

Scan detail

~250,000 trianglesincomplete coverage

surface color74 markers

Overview

1. Introduction2. Building a model3. Synthesis & editing

Overview

1. Introduction2. Building a model3. Synthesis & editing

The Correspondence Problem

Matching algorithm

scantemplate

Find the shape that:

1. Matches the template markers to the scanned markers

2. Moves template vertices to scanned surface

3. Minimizes the deformation

Matching algorithm

Overview

1. Introduction2. Building a model3. Synthesis & editing

Statistical analysis

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

average male mean + PCA component #1

mean + PCA component #2

Statistical analysis

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

average male

Statistical analysis

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

x0y0z0x1y1z1x2

average male mean + PCA component #3

PCA reconstruction

Fitting to attributes

We can correlate the PCA reconstructions of our scanned people with known attributes:

-40

-20

0

20

40

60

1.5 1.7 1.9 2.1

Height (m)

Pri

nci

pal

co

mp

on

ent

#1

Fitting to attributes

Fitting to points Using the distribution of the PCA weights as a prior, we

can find the most likely person that fits a set of point constraints.

PCA variance

user constraint

optimized reconstruction

Summary

Contributions: - an algorithm for creating a consistent

mesh representation from range scan data.

- several ways to explore the variation in human body shape, and to synthesize and edit body models

Future work

- analyze shape variation between poses

Future work

- combine with anatomical models and physical simulation

Aubel 2003

+

Acknowledgments

- Kathleen Robinette and the CAESAR project - Ethel Evans - Domi Pitturo - Daniel Wood

- NSF - NSERC - Microsoft Research, Electronic Arts, Sony - University of Washington Animation Research

Labs

2004-01-2188