• Mi Re-Unir
    Búsqueda Avanzada
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Ver ítem 
    •   Inicio
    • UNIR REVISTAS
    • Revista IJIMAI
    • 2019
    • vol. 5, nº 7, december 2019
    • Ver ítem
    •   Inicio
    • UNIR REVISTAS
    • Revista IJIMAI
    • 2019
    • vol. 5, nº 7, december 2019
    • Ver ítem

    Gesture Recognition of RGB and RGB-D Static Images Using Convolutional Neural Networks

    Autor: 
    González-Crespo, Rubén
    ;
    Verdú, Elena
    ;
    Khari, Manju
    ;
    Garg, Aditya Kumar
    Fecha: 
    12/2019
    Palabra clave: 
    image processing; gesture recognition; sign language; convolutional neural network (CNN); IJIMAI
    Revista / editorial: 
    International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/12662
    DOI: 
    http://doi.org/10.9781/ijimai.2019.09.002
    Dirección web: 
    https://www.ijimai.org/journal/bibcite/reference/2738
    Open Access
    Resumen:
    In this era, the interaction between Human and Computers has always been a fascinating field. With the rapid development in the field of Computer Vision, gesture based recognition systems have always been an interesting and diverse topic. Though recognizing human gestures in the form of sign language is a very complex and challenging task. Recently various traditional methods were used for performing sign language recognition but achieving high accuracy is still a challenging task. This paper proposes a RGB and RGB-D static gesture recognition method by using a fine-tuned VGG19 model. The fine-tuned VGG19 model uses a feature concatenate layer of RGB and RGB-D images for increasing the accuracy of the neural network. Finally, on an American Sign Language (ASL) Recognition dataset, the authors implemented the proposed model. The authors achieved 94.8% recognition rate and compared the model with other CNN and traditional algorithms on the same dataset.
    Mostrar el registro completo del ítem
    Ficheros en el ítem
    icon
    Nombre: ijimai20195_7_2_pdf_18405.pdf
    Tamaño: 785.5Kb
    Formato: application/pdf
    Ver/Abrir
    Este ítem aparece en la(s) siguiente(s) colección(es)
    • Artículos Científicos WOS y SCOPUS
    • vol. 5, nº 7, december 2019

    Estadísticas de uso

    Año
    2012
    2013
    2014
    2015
    2016
    2017
    2018
    2019
    2020
    2021
    2022
    2023
    2024
    2025
    Vistas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    53
    57
    129
    58
    Descargas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    16
    19
    34
    34

    Ítems relacionados

    Mostrando ítems relacionados por Título, autor o materia.

    • Feature based video stabilization based on boosted HAAR Cascade and representative point matching algorithm 

      Raj, Rohit; Rajiv, Pooshkar; Kumar, Prabhat; Khari, Manju; Verdú, Elena ; González-Crespo, Rubén ; Manogarane, Gunasekaran (Image and Vision Computing, 09/2020)
      The success of handheld video capturing devices has further fueled the need of improved video stabilization. The videos often contain many foreground facial features like eyes, nose etc. These foreground features can be ...
    • Performance analysis of six meta-heuristic algorithms over automated test suite generation for path coverage-based optimization 

      Khari, Manju; Sinha, Anunay; Verdú, Elena ; González-Crespo, Rubén (Soft Computing, 10/2019)
      There exists a direct need to automate the process of test suite generation to get the most optimal results as testing accounts for more than 40% of total cost. One method to solve this problem is the use of meta-heuristic ...
    • Fast single image haze removal method for inhomogeneous environment using variable scattering coefficient 

      Gupta, Rashmi; Khari, Manju; Gupta, Vipul; Verdú, Elena ; Wu, Xing; Herrera-Viedma, Enrique; González-Crespo, Rubén (CMES - Computer Modeling in Engineering and Sciences, 2020)
      The images capture in a bad environment usually loses its fidelity and contrast. As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the ...

    Mi cuenta

    AccederRegistrar

    ¿necesitas ayuda?

    Manual de UsuarioContacto: reunir@unir.net

    Listar

    todo Re-UnirComunidades y coleccionesPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de accesoEsta colecciónPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de acceso






    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja
     
    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja