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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.

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Presentation on theme: "Exploring the space of human body shapes: data-driven synthesis under anthropometric control Brett Allen Brian Curless Zoran Popović University of Washington."— Presentation transcript:

1 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

2 Motivation Traditional anthropometry has focused on sets of one-dimensional measurements.

3 Motivation Full body shape capture promises to advance the state of the art. ?

4 CAESAR Civilian 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).

5 Scan detail ~250,000 triangles incomplete coverage surface color 74 markers

6 Overview 1. Introduction 2. Building a model 3. Synthesis & editing

7 Overview 1. Introduction 2. Building a model 3. Synthesis & editing

8 The Correspondence Problem

9 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

10 Matching algorithm

11 Overview 1. Introduction 2. Building a model 3. Synthesis & editing

12 Statistical analysis x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 average male mean + PCA component #1

13 mean + PCA component #2 Statistical analysis x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 average male

14 Statistical analysis x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 x0x0 y0y0 z0z0 x1x1 y1y1 z1z1 x2x2 average male mean + PCA component #3

15 PCA reconstruction

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

17 Fitting to attributes

18 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 varianceuser constraint optimized reconstruction

19 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

20 Future work - analyze shape variation between poses

21 Future work - combine with anatomical models and physical simulation Aubel 2003 +

22 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


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