Dynamic Hand Recognition for Indonesian Sign Language (SIBI) using Leap Motion Control base on Euclidean Distance and Naïve Bayes Classifier

EasyChair Preprint 796

Abstract

Most deaf children are born into hearing families and the majority do not begin their Sign Language learning before age 3-6 in school. As children learning Sign Language from infancy show higher language proficiency than those who do not, it underlines the importance of hearing parents learning how to sign.  The research method in naïve bayes algorithm, in order to classify 26 alphabet letter of Indonesian sign language including letter J and Z which using gesture for describe it. The Leap Motion controller is a consumer gesture sensor aimed to augment a user’s interactive experience with their computer. It use for derive feature data from the deaf children gesture recording to set data in application. The accuracy level of the test result reached 96%.

Keyphrases: Dynamic Hand Recognition, Euclidean distance, Gaussian Naive Bayes, Indonesian Sign Language, Leap Motion Control, Naïve Bayes

@booklet{EasyChair:796,
  author    = {Ridwang and Syafaruddin and Amil Ahmad Ilham and Ingrid Nurtanio},
  title     = {Dynamic Hand Recognition for Indonesian Sign Language (SIBI) using Leap Motion Control base on Euclidean Distance and Naïve Bayes Classifier},
  howpublished = {EasyChair Preprint 796},
  year      = {EasyChair, 2019}}