Fuzzy hand posture models in man-machine communication

András A. Tóth, Balázs Tusor, Annamária R. Várkonyi-Kóczy

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Ever since the assemblage of the first computer, efforts have been made to improve the way people could use machines. This ambition is still present nowadays: indeed, intuitively operated systems are currently under intensive research. Intelligent Space (or iSpace) based systems are good examples: they strive to be comfortable and easy to use, even without demanding technical knowledge from their users. However, their aim is not limited to this: in fact, their ultimate goal is to achieve an intelligent environment for higher quality, natural, and easy to follow lifestyle. The system described in this chapter can be used to create a new, intuitive man-machine interface for iSpace applications. The solution exploits one of the basic human skills, namely the ability to assume various hand postures. The proposed system first processes the frames of a stereo camera pair and builds a model of the hand posture visible on the images and then classifies this model into one of the previously stored hand posture models, by using neural networks and fuzzy reasoning.

Original languageEnglish
Title of host publicationComputational Intelligence in Engineering
EditorsImre Rudas
Pages229-245
Number of pages17
DOIs
Publication statusPublished - Nov 3 2010

Publication series

NameStudies in Computational Intelligence
Volume313
ISSN (Print)1860-949X

    Fingerprint

Keywords

  • Image Processing
  • Intelligent Space
  • Intuitive User Interface
  • Smart Environments
  • Soft Computing
  • Ubiquitous Computing

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Tóth, A. A., Tusor, B., & Várkonyi-Kóczy, A. R. (2010). Fuzzy hand posture models in man-machine communication. In I. Rudas (Ed.), Computational Intelligence in Engineering (pp. 229-245). (Studies in Computational Intelligence; Vol. 313). https://doi.org/10.1007/978-3-642-15220-7_19