Enhancing motion capture performance by means of an internal anthropometric skeleton model

Matthias Weber, Thomas Alexander, Hani Ben Amor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most motion tracking algorithms rely on an initial skeleton model that has already been fitted to a special posture setup. However, such a first identification of markers often requires multiple manual actions of a designer. To automate this process, a novel approach for adapting a basic skeleton model to empirical motion capture data is presented. The approach is based on the anthropometric dimensions of a subject and subsequent tree-based skeleton fitting. It generates a tree representation of different possible skeleton configurations. The tree is annotated with costs based on discrepancies between markers and anatomic landmarks. A computation of the least cost path through the tree automatically results in an optimal fitting of the observed markers to the given anthropometric data of the subject.

Original languageEnglish (US)
Title of host publicationSAE Technical Papers
DOIs
StatePublished - 2008
Externally publishedYes
EventDigital Human Modeling for Design and Engineering Conference and Exhibition - Pittsburgh, PA, United States
Duration: Jun 17 2008Jun 19 2008

Other

OtherDigital Human Modeling for Design and Engineering Conference and Exhibition
CountryUnited States
CityPittsburgh, PA
Period6/17/086/19/08

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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