Home / Issues / 3.2006 / Automatic Data Normalization and Parameterization for Optical Motion Tracking
Document Actions

Citation and metadata

Back to the article.

Recommended citation

Sadip Dessai, Alexander Hornung, and Leif Kobbelt, Automatic Data Normalization and Parameterization for Optical Motion Tracking. JVRB - Journal of Virtual Reality and Broadcasting, 3(2006), no. 3. (urn:nbn:de:0009-6-5481)

Download Citation

Endnote

%0 Journal Article
%T Automatic Data Normalization and Parameterization for Optical Motion Tracking
%A Dessai, Sadip
%A Hornung, Alexander
%A Kobbelt, Leif
%J JVRB - Journal of Virtual Reality and Broadcasting
%D 2006
%V 3(2006)
%N 3
%@ 1860-2037
%F dessai2006
%X Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalizationstep aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generatea compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.
%L 004
%K Automatic Normalization and Parameterization
%K Optical Motion Capture
%R 10.20385/1860-2037/3.2006.3
%U http://nbn-resolving.de/urn:nbn:de:0009-6-5481
%U http://dx.doi.org/10.20385/1860-2037/3.2006.3
Download

Bibtex

@Article{dessai2006,
  author = 	"Dessai, Sadip
		and Hornung, Alexander
		and Kobbelt, Leif",
  title = 	"Automatic Data Normalization and Parameterization for Optical Motion Tracking",
  journal = 	"JVRB - Journal of Virtual Reality and Broadcasting",
  year = 	"2006",
  volume = 	"3(2006)",
  number = 	"3",
  keywords = 	"Automatic Normalization and Parameterization; Optical Motion Capture",
  abstract = 	"Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalizationstep aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generatea compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.",
  issn = 	"1860-2037",
  doi = 	"10.20385/1860-2037/3.2006.3",
  url = 	"http://nbn-resolving.de/urn:nbn:de:0009-6-5481"
}
Download

RIS

TY  - JOUR
AU  - Dessai, Sadip
AU  - Hornung, Alexander
AU  - Kobbelt, Leif
PY  - 2006
DA  - 2006//
TI  - Automatic Data Normalization and Parameterization for Optical Motion Tracking
JO  - JVRB - Journal of Virtual Reality and Broadcasting
VL  - 3(2006)
IS  - 3
KW  - Automatic Normalization and Parameterization
KW  - Optical Motion Capture
AB  - Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalizationstep aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generatea compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.
SN  - 1860-2037
UR  - http://nbn-resolving.de/urn:nbn:de:0009-6-5481
DO  - 10.20385/1860-2037/3.2006.3
ID  - dessai2006
ER  -
Download

Wordbib

<?xml version="1.0" encoding="UTF-8"?>
<b:Sources SelectedStyle="" xmlns:b="http://schemas.openxmlformats.org/officeDocument/2006/bibliography"  xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" >
<b:Source>
<b:Tag>dessai2006</b:Tag>
<b:SourceType>ArticleInAPeriodical</b:SourceType>
<b:Year>2006</b:Year>
<b:PeriodicalTitle>JVRB - Journal of Virtual Reality and Broadcasting</b:PeriodicalTitle>
<b:Volume>3(2006)</b:Volume>
<b:Issue>3</b:Issue>
<b:Url>http://nbn-resolving.de/urn:nbn:de:0009-6-5481</b:Url>
<b:Url>http://dx.doi.org/10.20385/1860-2037/3.2006.3</b:Url>
<b:Author>
<b:Author><b:NameList>
<b:Person><b:Last>Dessai</b:Last><b:First>Sadip</b:First></b:Person>
<b:Person><b:Last>Hornung</b:Last><b:First>Alexander</b:First></b:Person>
<b:Person><b:Last>Kobbelt</b:Last><b:First>Leif</b:First></b:Person>
</b:NameList></b:Author>
</b:Author>
<b:Title>Automatic Data Normalization and Parameterization for Optical Motion Tracking</b:Title>
<b:Comments>Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalizationstep aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generatea compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.</b:Comments>
</b:Source>
</b:Sources>
Download

ISI

PT Journal
AU Dessai, S
   Hornung, A
   Kobbelt, L
TI Automatic Data Normalization and Parameterization for Optical Motion Tracking
SO JVRB - Journal of Virtual Reality and Broadcasting
PY 2006
VL 3(2006)
IS 3
DI 10.20385/1860-2037/3.2006.3
DE Automatic Normalization and Parameterization; Optical Motion Capture
AB Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalizationstep aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generatea compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.
ER
Download

Mods

<mods>
  <titleInfo>
    <title>Automatic Data Normalization and Parameterization for Optical Motion Tracking</title>
  </titleInfo>
  <name type="personal">
    <namePart type="family">Dessai</namePart>
    <namePart type="given">Sadip</namePart>
  </name>
  <name type="personal">
    <namePart type="family">Hornung</namePart>
    <namePart type="given">Alexander</namePart>
  </name>
  <name type="personal">
    <namePart type="family">Kobbelt</namePart>
    <namePart type="given">Leif</namePart>
  </name>
  <abstract>Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalization
step aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generate
a compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.</abstract>
  <subject>
    <topic>Automatic Normalization and Parameterization</topic>
    <topic>Optical Motion Capture</topic>
  </subject>
  <classification authority="ddc">004</classification>
  <relatedItem type="host">
    <genre authority="marcgt">periodical</genre>
    <genre>academic journal</genre>
    <titleInfo>
      <title>JVRB - Journal of Virtual Reality and Broadcasting</title>
    </titleInfo>
    <part>
      <detail type="volume">
        <number>3(2006)</number>
      </detail>
      <detail type="issue">
        <number>3</number>
      </detail>
      <date>2006</date>
    </part>
  </relatedItem>
  <identifier type="issn">1860-2037</identifier>
  <identifier type="urn">urn:nbn:de:0009-6-5481</identifier>
  <identifier type="doi">10.20385/1860-2037/3.2006.3</identifier>
  <identifier type="uri">http://nbn-resolving.de/urn:nbn:de:0009-6-5481</identifier>
  <identifier type="citekey">dessai2006</identifier>
</mods>
Download

Full Metadata

Bibliographic Citation JVRB, 3(2006), no. 3.
Title

Automatic Data Normalization and Parameterization for Optical Motion Tracking (eng)
Author Sadip Dessai, Alexander Hornung, Leif Kobbelt
Language eng
Abstract Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalization step aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generate a compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.
Subject Automatic Normalization and Parameterization, Optical Motion Capture
Classified Subjects
ddc
  • 004, Informatik
swd
  • 4546181-8, Motion Capturing
  • 4206017-5, Normalization
DDC 004
Rights DPPL
URN: urn:nbn:de:0009-6-5481
DOI https://doi.org/10.20385/1860-2037/3.2006.3