A discrete Reeb graph approach for the segmentation of human body scans

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

55 Scopus citations

Abstract

Segmentation of 3D human body (HB) scan is a very challenging problem in applications exploiting human scan data. To tackle this problem, we propose a topological approach based on discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to unorganized cloud of 3D points. The essence of the approach is detecting critical nodes in the DRG thus permitting the extraction of branches that represent the body parts. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, moderate reference change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method.

Original languageBritish English
Title of host publicationProceedings - 4th International Conference on 3-D Digital Imaging and Modeling, 3DIM 2003
PublisherIEEE Computer Society
Pages378-385
Number of pages8
ISBN (Electronic)0769519911
DOIs
StatePublished - 2003
Event4th International Conference on 3-D Digital Imaging and Modeling, 3DIM 2003 - Banff, Canada
Duration: 6 Oct 200310 Oct 2003

Publication series

NameProceedings of International Conference on 3-D Digital Imaging and Modeling, 3DIM
Volume2003-January
ISSN (Print)1550-6185

Conference

Conference4th International Conference on 3-D Digital Imaging and Modeling, 3DIM 2003
Country/TerritoryCanada
CityBanff
Period6/10/0310/10/03

Keywords

  • Arm
  • Data mining
  • Educational institutions
  • Humans
  • Image segmentation
  • Leg
  • Noise robustness
  • Noise shaping
  • Shape
  • Torso

Fingerprint

Dive into the research topics of 'A discrete Reeb graph approach for the segmentation of human body scans'. Together they form a unique fingerprint.

Cite this