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Author, Editor

Author(s):

Gehrig, Stefan
Hernán, Badino
Gall, Jürgen

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Not MPG Author(s):

Gehrig, Stefan
Hernán, Badino

Editor(s):

Klette, Reinhard
Metaxas, Dimitris
Rosenhahn, Bodo

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Not MPII Editor(s):

Klette, Reinhard
Metaxas, Dimitris

BibTeX cite key*:

Gall2007c

Title, Booktitle

Title*:

Accurate and Model-Free Pose Estimation of Crash Test Dummies

Booktitle*:

Human Motion - Understanding, Modeling, Capture and Animation

Chapter:


Series:


Language:

English

Publisher

Name*:

Springer

URL:


Address*:

Heidelberg

Publication Type:


Vol, No, pp., Year

Volume:


Number:


Edition:


Pages*:

453-473

Month:


VG Wort Pages:

23

ISBN:

978-1-4020-6692-4

Year*:

2008

Abstract, Links, ©

Note:


LaTeX Abstract:

In this chapter, we present a model-free pose estimation algorithm to estimate the relative pose of a rigid object. In the context of human motion, a rigid object can be either a limb, the head, or the back. In most pose estimation algorithms, the object
of interest covers a large image area. We focus on pose estimation of objects covering a field of view of less than
5$^\circ$\ by 5$^\circ$\ using stereo vision.

With this new algorithm suitable for small objects, we
investigate the effect of the object size on the pose accuracy.
In addition, we introduce an object tracking technique that is insensitive
to partial occlusion. We are particularly interested in human motion
in this context focusing on crash test dummies.

The main application for this method is the analysis of crash video sequences.
For a human motion capture system, a connection of the various limbs can be
done in an additional step.
The ultimate goal is to fully obtain the motion of crash test dummies
in a vehicle crash. This would give information on which body part is
exposed to what kind of forces and rotational forces could be
determined as well. Knowing all this, car manufacturers can optimize
the passive safety components to reduce forces on the dummy and
ultimately on the real vehicle passengers.
Since
camera images for crash videos contain the whole crash vehicle, the size of the crash
test dummies is relatively small in our experiments.

For these experiments, mostly high-speed cameras with high resolution
are used. However, the method described here
easily extends to real-time robotics
applications with smaller VGA-size images,
where relative pose estimation is needed, {e.g.}\ for manipulator control.

URL Abstract:


Tags, Keywords:


Copyright Message:


HyperLinks / References / URLs:


Personal Comments:


Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort
BibTeX Entry:
@INBOOK{Gall2007c,
AUTHOR = {Gehrig, Stefan and Hern{\'a}n, Badino and Gall, J{\"u}rgen},
EDITOR = {Klette, Reinhard and Metaxas, Dimitris and Rosenhahn, Bodo},
TITLE = {Accurate and Model-Free Pose Estimation of Crash Test Dummies},
BOOKTITLE = {Human Motion - Understanding, Modeling, Capture and Animation},
PUBLISHER = {Springer},
YEAR = {2008},
PAGES = {453--473},
ADDRESS = {Heidelberg},
ISBN = {978-1-4020-6692-4},
}


Entry last modified by Anja Becker, 04/07/2008
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Editor(s)
Jürgen Gall
Created
04/24/2007 09:28:58 PM
Revisions
5.
4.
3.
2.
1.
Editor(s)
Anja Becker
Jürgen Gall
Jürgen Gall
Jürgen Gall
Jürgen Gall
Edit Dates
07.04.2008 10:29:13
12/11/2007 05:51:10 PM
04/27/2007 03:26:51 PM
04/27/2007 03:11:05 PM
04/24/2007 09:34:00 PM
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