Detecting hand-palm orientation and hand shapes for sign language gesture recognition using 3D images

2012 ◽  
Author(s):  
Lalit K. Phadtare ◽  
Raja S. Kushalnagar ◽  
Nathan D. Cahill
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
3D Images

Technological Aids for Deaf and Mute in Modern World

2020 ◽  
Vol 14 ◽  
Author(s):  
Vasu Mehra ◽  
Dhiraj Pandey ◽  
Aayush Rastogi ◽  
Aditya Singh ◽  
Harsh Preet Singh
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Recognition System ◽  
Modern World ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Background Elimination ◽  
Sign Recognition ◽  
Technological Advances ◽  
Better Than

Background:: People suffering from hearing and speaking disabilities have a few ways of communicating with other people. One of these is to communicate through the use of sign language. Objective:: Developing a system for sign language recognition becomes essential for deaf as well as a mute person. The recognition system acts as a translator between a disabled and an able person. This eliminates the hindrances in exchange of ideas. Most of the existing systems are very poorly designed with limited support for the needs of their day to day facilities. Methods:: The proposed system embedded with gesture recognition capability has been introduced here which extracts signs from a video sequence and displays them on screen. On the other hand, a speech to text as well as text to speech system is also introduced to further facilitate the grieved people. To get the best out of human computer relationship, the proposed solution consists of various cutting-edge technologies and Machine Learning based sign recognition models which have been trained by using Tensor Flow and Keras library. Result:: The proposed architecture works better than several gesture recognition techniques like background elimination and conversion to HSV because of sharply defined image provided to the model for classification. The results of testing indicate reliable recognition systems with high accuracy that includes most of the essential and necessary features for any deaf and dumb person in his/her day to day tasks. Conclusion:: It’s the need of current technological advances to develop reliable solutions which can be deployed to assist deaf and dumb people to adjust to normal life. Instead of focusing on a standalone technology, a plethora of them have been introduced in this proposed work. Proposed Sign Recognition System is based on feature extraction and classification. The trained model helps in identification of different gestures.

Alphabetical Gesture Recognition of American Sign Language using E-Voice Smart Glove

2020 ◽  
Author(s):  
Muhammad Saad Amin ◽  
Muhammad Talha Amin ◽  
Muhammad Yasir Latif ◽  
Ali Asghar Jathol ◽  
Nisar Ahmed ◽  
...  
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Gesture Recognition ◽  
American Sign
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