Peruvian sign language recognition using low resolution cameras

Bryan Berru-Novoa, Ricardo Gonzalez-Valenzuela, Pedro Shiguihara-Juarez

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

6 Citas (Scopus)

Resumen

The recognition of sign language gesture through image processing and Machine Learning has been widely studied in recent years. This article presents a dataset consisting of 2400 images of the static gestures of the Peruvian sign language alphabet, in addition to applying it to a hand gesture recognition system using low resolution cameras. For the gesture recognition, the Histogram Oriented Gradient feature descriptor was used, along with 4 classification algorithms. The results showed that Histogram Oriented Gradient, along with Support Vector Machine, got the best result with a 89.46% accuracy and the system was able to recognize the gestures with variations of translation, rotation and scale.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538654903
DOI
EstadoPublicada - 6 nov. 2018
Publicado de forma externa
Evento25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018 - Lima, Perú
Duración: 8 ago. 201810 ago. 2018

Serie de la publicación

NombreProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018

Conferencia

Conferencia25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
País/TerritorioPerú
CiudadLima
Período8/08/1810/08/18

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