ANN based Indian Sign Language numerals recognition using the leap motion controller

2016 ◽  
Author(s):  
Deepali Naglot ◽  
Milind Kulkarni
Keyword(s):  
Sign Language ◽  
Leap Motion ◽  
Motion Controller ◽  
Leap Motion Controller ◽  
Indian Sign Language

scholarly journals American Sign Language Recognition Using Leap Motion Controller with Machine Learning Approach

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3554 ◽  
Author(s):  
Teak-Wei Chong ◽  
Boon-Giin Lee
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Recognition System ◽  
Support Vector ◽  
Leap Motion ◽  
American Sign ◽  
Language Recognition ◽  
Motion Controller ◽  
Sign Language Recognition ◽  
Leap Motion Controller

Sign language is intentionally designed to allow deaf and dumb communities to convey messages and to connect with society. Unfortunately, learning and practicing sign language is not common among society; hence, this study developed a sign language recognition prototype using the Leap Motion Controller (LMC). Many existing studies have proposed methods for incomplete sign language recognition, whereas this study aimed for full American Sign Language (ASL) recognition, which consists of 26 letters and 10 digits. Most of the ASL letters are static (no movement), but certain ASL letters are dynamic (they require certain movements). Thus, this study also aimed to extract features from finger and hand motions to differentiate between the static and dynamic gestures. The experimental results revealed that the sign language recognition rates for the 26 letters using a support vector machine (SVM) and a deep neural network (DNN) are 80.30% and 93.81%, respectively. Meanwhile, the recognition rates for a combination of 26 letters and 10 digits are slightly lower, approximately 72.79% for the SVM and 88.79% for the DNN. As a result, the sign language recognition system has great potential for reducing the gap between deaf and dumb communities and others. The proposed prototype could also serve as an interpreter for the deaf and dumb in everyday life in service sectors, such as at the bank or post office.

scholarly journals Feature Optimization on Dual Leap Motion Controller for Indonesian Sign Language

2021 ◽  
Vol 328 ◽  
pp. 03006
Author(s):  
Syaiful Nugraha ◽  
Rachmat ◽  
Teddy Istanto ◽  
Agus Prayitno
Keyword(s):  
Sign Language ◽  
Sensor Technology ◽  
Leap Motion ◽  
Motion Controller ◽  
Persons With Disabilities ◽  
Leap Motion Controller ◽  
Average Accuracy ◽  
Feature Optimization ◽  
Increase In Accuracy ◽  
The Given

Sign language is a language formed by a combination of finger, hand, body movements and facial expressions used by persons with disabilities such as deaf and speech impaired. One of these sign language recognitions is recognition using Leap Motion Controller (LMC) sensor technology. In addition to the sign language that is formed has diversity such as folded fingers, hidden fingers, indonesian sign forms also have characteristics and shapes that are almost similar to one another. The LMC sensor is not always able to recognize all forms of signs properly. In this study, optimization is proposed at the feature level where optimization aims to provide more detailed features and characteristics of each sign language formed. The stages of the process are designing the layout of the sensors, adding features and combining feature data from each sensor. The test of the feature optimization on this dual LMC sensor can provide an increase in the recognition accuracy of the given Indonesian sign language. The Indonesian sign language can be recognized well with an average accuracy of 87.24% and the optimization carried out is able to produce an increase in accuracy of up to 2.88%.

scholarly journals Exploiting Recurrent Neural Networks and Leap Motion Controller for the Recognition of Sign Language and Semaphoric Hand Gestures

2019 ◽  
Vol 21 (1) ◽  
pp. 234-245 ◽  
Author(s):  
Danilo Avola ◽  
Marco Bernardi ◽  
Luigi Cinque ◽  
Gian Luca Foresti ◽  
Cristiano Massaroni
Keyword(s):  
Neural Networks ◽  
Sign Language ◽  
Recurrent Neural Networks ◽  
Leap Motion ◽  
Motion Controller ◽  
Hand Gestures ◽  
Leap Motion Controller
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