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

    Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

    2 Citas (Scopus)

    Resumen

    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.

    Idioma originalInglés
    Páginas (desde-hasta)99-108
    Número de páginas10
    PublicaciónAutomatika
    Volumen61
    N.º1
    DOI
    EstadoPublicada - 2 ene 2020

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