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Author, Editor

Author(s):

Helten, Thomas
Müller, Meinard
Seidel, Hans-Peter
Theobalt, Christian

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Not MPG Author(s):

Müller, Meinard

Editor(s):





BibTeX cite key*:

HeltenMuSeTh13_InertialDepthTracker_ICCV

Title, Booktitle

Title*:

Real-time Body Tracking with One Depth Camera and Inertial Sensors

Booktitle*:

The IEEE International Conference on Computer Vision (ICCV)

Event, URLs

URL of the conference:

http://www.iccv2013.org/

URL for downloading the paper:

http://resources.mpi-inf.mpg.de/InertialDepthTracker/downloads/InertialDepthTracker.pdf

Event Address*:

Sydney, Australia

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

1 December 2013

Event End Date:

8 December 2013

Publisher

Name*:


This proceedings has no publisher!

URL:


Address*:

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Type:


Vol, No, Year, pp.

Series:

The IEEE International Conference on Computer Vision (ICCV)

Volume:


Number:


Month:

December

Pages:

1105-1112

Year*:

2013

VG Wort Pages:


ISBN/ISSN:


Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

In recent years, the availability of inexpensive depth cameras, such as the Microsoft Kinect, has
boosted the research in monocular full body skeletal pose tracking.
Unfortunately, existing trackers often fail to capture poses where a single camera
provides insufficient data, such as non-frontal poses, and all other poses with body part occlusions.
In this paper, we present a novel sensor fusion approach for real-time full body tracking that succeeds in such difficult situations.
It takes inspiration from previous tracking solutions, and combines a generative tracker and a discriminative tracker
retrieving closest poses in a database. In contrast to previous work, both trackers employ data from a low number of inexpensive
body-worn inertial sensors. These sensors provide reliable and complementary information when the monocular depth information alone is not sufficient.
We also contribute by new algorithmic solutions to best fuse depth and inertial data in both trackers. One is a new visibility model to determine global body pose, occlusions and usable depth correspondences and to decide what data modality to use for discriminative tracking. We also
contribute with a new inertial-based pose retrieval, and an adapted late fusion step to calculate the
final body pose.



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Access Level:

Internal

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Audience:

experts only

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{HeltenMuSeTh13_InertialDepthTracker_ICCV,
AUTHOR = {Helten, Thomas and M{\"u}ller, Meinard and Seidel, Hans-Peter and Theobalt, Christian},
TITLE = {Real-time Body Tracking with One Depth Camera and Inertial Sensors},
BOOKTITLE = {The IEEE International Conference on Computer Vision (ICCV)},
YEAR = {2013},
PAGES = {1105--1112},
SERIES = {The IEEE International Conference on Computer Vision (ICCV)},
ADDRESS = {Sydney, Australia},
MONTH = {December},
}


Entry last modified by Thomas Helten, 01/30/2014
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Editor(s)
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Created
01/06/2014 10:34:27 AM
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Editor
Thomas Helten



Edit Date
06.01.2014 10:34:27