Volumetric Representation of Semantically Segmented Human Body Parts Using Superquadrics

Ryo Hachiuma, Hideo Saito

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

3 Citations (Scopus)

Abstract

Superquadrics are one of the ideal shape representations for adapting various kinds of primitive shapes with a single equation. This paper revisits the task of representing a 3D human body with multiple superquadrics. As a single superquadric surface can only represent symmetric primitive shapes, we present a method that segments the human body into body parts to estimate their superquadric parameters. Moreover, we propose a novel initial parameter estimation method by using 3D skeleton joints. The results show that superquadric parameters are estimated, which represent human body parts volumetrically.

Original languageEnglish
Title of host publicationVirtual Reality and Augmented Reality - 16th EuroVR International Conference, EuroVR 2019, Proceedings
EditorsPatrick Bourdot, Victoria Interrante, Luciana Nedel, Nadia Magnenat-Thalmann, Gabriel Zachmann
PublisherSpringer
Pages52-61
Number of pages10
ISBN (Print)9783030319076
DOIs
Publication statusPublished - 2019
Event16th International Conference on Virtual Reality and Augmented Reality, EuroVR 2019 - Tallinn, Estonia
Duration: 2019 Oct 232019 Oct 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11883 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Virtual Reality and Augmented Reality, EuroVR 2019
Country/TerritoryEstonia
CityTallinn
Period19/10/2319/10/25

Keywords

  • Semantic segmentation
  • Superquadrics
  • Volumetric representation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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