Now showing items 1-6 of 6
Spatio-Temporal Feature-Extraction Techniques for Isolated Gesture Recognition in Arabic Sign Language
This paper presents various spatio-temporal feature-extraction techniques with applications to online and offline recognitions of isolated Arabic Sign Language gestures. The temporal features of a video-based gesture are ...
Glove-Based Continuous Arabic Sign Language Recognition in User-Dependent Mode
In this paper we propose a glove-based Arabic sign language recognition system using a novel technique for sequential data classification. We compile a sensor-based dataset of 40 sentences using an 80-word lexicon. In the ...
Telescopic Vector Composition and Polar Accumulated Motion Residuals for Feature Extraction in Arabic Sign Language Recognition
This work introduces two novel approaches for feature extraction applied to video-based Arabic sign language recognition, namely, motion representation through motion estimation and motion representation through motion ...
Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition
This paper proposes a novel approach to continuous Arabic Sign Language recognition. We use a dataset which contains 40 sentences composed from 80 sign language words. The dataset is collected using sensor-based gloves. ...
Multiple Proposals for Continuous Arabic Sign Language Recognition
The deaf community relies on sign language as the primary means of communication. For the millions of people around the world who suffer from hearing loss, interaction with hearing people is quite difficult. The main ...
User-independent recognition of Arabic sign language for facilitating communication with the deaf community
This paper presents a solution for user-independent recognition of isolated Arabic Sign language gestures. The video based gestures are preprocessed to segment out the hands of the signer based on color segmentation of the ...