Albanian Sign Language (AlbSL) Number Recognition from Both Hand's Gestures Acquired by Kinect Sensors
This addresses the lack of systems for AlbSL recognition, but it is incremental as it applies existing methods to a new language domain.
The paper tackles the problem of recognizing Albanian Sign Language (AlbSL) number signs from both hands using Kinect sensors, achieving 91% accuracy and processing 55 frames per second in real-time.
Albanian Sign Language (AlbSL) is relatively new and until now there doesn't exist a system that is able to recognize Albanian signs by using natural user interfaces (NUI). The aim of this paper is to present a real-time gesture recognition system that is able to automatically recognize number signs for Albanian Sign Language, captured from signer's both hands. Kinect device is used to obtain data streams. Every pixel generated from Kinect device contains depth data information which is used to construct a depth map. Hands segmentation process is performed by applying a threshold constant to depth map. In order to differentiate signer's hands a K-means clustering algorithm is applied to partition pixels into two groups corresponding to each signer's hands. Centroid distance function is calculated in each hand after extracting hand's contour pixels. Fourier descriptors, derived form centroid distance is used as a hand shape representation. For each number gesture there are 15 Fourier descriptors coefficients generated which represent uniquely that gesture. Every input data is compared against training data set by calculating Euclidean distance, using Fourier coefficients. Sign with the lowest Euclidean distance is considered as a match. The system is able to recognize number signs captured from one hand or both hands. When both signer's hands are used, some of the methodology processes are executed in parallel in order to improve the overall performance. The proposed system achieves an accuracy of 91% and is able to process 55 frames per second.