Hand features extractor using hand contour–a case study

Antonio Guadalupe Cruz Bautista, José Joel González-Barbosa, Juan Bautista Hurtado-Ramos, Francisco Javier Ornelas-Rodriguez, Erick Alejandro González-Barbosa

Research output: Contribution to journalArticle

Abstract

Hand gesture recognition is an important topic in natural user interfaces (NUI). Hand features extraction is the first step for hand gesture recognition. This work proposes a novel real time method for hand features recognition. In our framework we use three cameras and the hand region is extracted with the background subtraction method. Features like arm angle and fingers positions are calculated using Y variations in the vertical contour image. Wrist detection is obtained by calculating the bigger distance from a base line and the hand contour, giving the main features for the hand gesture recognition. Experiments on our own data-set of about 1800 images show that our method performs well and is highly efficient.

Original languageEnglish
Pages (from-to)99-108
Number of pages10
JournalAutomatika
Volume61
Issue number1
DOIs
StatePublished - 2 Jan 2020

Fingerprint

Gesture recognition
User interfaces
Feature extraction
Cameras
Experiments

Keywords

  • fingers
  • gesture
  • Hand
  • NUI
  • recognition

Cite this

Cruz Bautista, Antonio Guadalupe ; González-Barbosa, José Joel ; Hurtado-Ramos, Juan Bautista ; Ornelas-Rodriguez, Francisco Javier ; González-Barbosa, Erick Alejandro. / Hand features extractor using hand contour–a case study. In: Automatika. 2020 ; Vol. 61, No. 1. pp. 99-108.
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Hand features extractor using hand contour–a case study. / Cruz Bautista, Antonio Guadalupe; González-Barbosa, José Joel; Hurtado-Ramos, Juan Bautista; Ornelas-Rodriguez, Francisco Javier; González-Barbosa, Erick Alejandro.

In: Automatika, Vol. 61, No. 1, 02.01.2020, p. 99-108.

Research output: Contribution to journalArticle

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