FIST: A fast, implicit model of the human hand with semi-anatomical structures

Masato Nakada, Hélène Ballet, Issei Fujishiro

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

Abstract

There are many opportunities to draw human hands in computer graphics. The motion of internal organs within a human hand has a non-negligible effect on the natural change in the appearance of the hand's surface. In this work, we propose a method for expressing this change interactively with the use of an implicit model of a human hand that has semi-anatomical structures. The model is referred to as Fast, Implicit model with Semi-anatomical sTructures or FIST. In the FIST model, bones are modeled anatomically based on computed tomography imaging, while soft tissues are modeled artificially. It can be controlled only by specifying the angles of the joints. The proposed method can contribute to a compelling expression of the dynamism in such hand motions as grasping, pinching, and scratching in immersive virtual reality and games.

Original languageEnglish
Title of host publicationSIGGRAPH Asia 2018 Technical Briefs, SA 2018
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450360623
DOIs
Publication statusPublished - 2018 Dec 4
EventSIGGRAPH Asia 2018 Technical Briefs - International Conference on Computer Graphics and Interactive Techniques, SA 2018 - Tokyo, Japan
Duration: 2018 Dec 42018 Dec 7

Other

OtherSIGGRAPH Asia 2018 Technical Briefs - International Conference on Computer Graphics and Interactive Techniques, SA 2018
CountryJapan
CityTokyo
Period18/12/418/12/7

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Keywords

  • Human hand
  • Implicit modeling
  • Volume rendering

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software

Cite this

Nakada, M., Ballet, H., & Fujishiro, I. (2018). FIST: A fast, implicit model of the human hand with semi-anatomical structures. In SIGGRAPH Asia 2018 Technical Briefs, SA 2018 [a34] Association for Computing Machinery, Inc. https://doi.org/10.1145/3283254.3283280