scholarly journals Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields

Sensors ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 135-147 ◽  
Author(s):  
Hee-Deok Yang
Keyword(s):  
Sign Language ◽  
Random Fields ◽  
Conditional Random Fields ◽  
Kinect Sensor ◽  
Language Recognition ◽  
Sign Language Recognition

scholarly journals Arabic Sign Language Recognition Using Kinect Sensor

2018 ◽  
Vol 15 (2) ◽  
pp. 57-67 ◽  
Author(s):  
Abdel-Gawad Abdel-Rabouh Abdel-Samie ◽  
F.A. Elmisery ◽  
Ayman M.Brisha ◽  
Ahmed H. Khalil
Keyword(s):  
Sign Language ◽  
Kinect Sensor ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Arabic Sign Language

scholarly journals Sign language recognition using Kinect sensor based on color stream and skeleton points

2021 ◽  
Vol 47 (2) ◽  
pp. 769-778
Author(s):  
Isack Bulugu
Keyword(s):  
Sign Language ◽  
Recognition Accuracy ◽  
Learning Algorithm ◽  
Recognition System ◽  
Kinect Sensor ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Sign Recognition ◽  
Average Accuracy ◽  
High Recognition Accuracy

This paper presents a sign language recognition system based on color stream and skeleton points. Several approaches have been established to address sign language recognition problems. However, most of the previous approaches still have poor recognition accuracy. The proposed approach uses Kinect sensor based on color stream and skeleton points from the depth stream to improved recognition accuracy. Techniques within this approach use hand trajectories and hand shapes in combating sign recognition challenges. Therefore, for a particular sign a representative feature vector is extracted, which consists of hand trajectories and hand shapes. A sparse dictionary learning algorithm, Label Consistent K-SVD (LC-KSVD) is applied to obtain a discriminative dictionary. Based on that, the system was further developed to a new classification approach for better results. The proposed system was fairly evaluated based on 21 sign words including one-handed signs and two-handed signs. It was observed that the proposed system gets high recognition accuracy of 98.25%, and obtained an average accuracy of 95.34% for signer independent recognition. Keywords: Sign language, Color stream, Skeleton points, Kinect sensor, Discriminative dictionary.

INDIAN SIGN LANGUAGE RECOGNITION SYSTEM USING OPENPOSE

2019 ◽  
Vol 7 (2) ◽  
pp. 43
Author(s):  
MALHOTRA POOJA ◽  
K. MANIAR CHIRAG ◽  
V. SANKPAL NIKHIL ◽  
R. THAKKAR HARDIK ◽  
◽  
...  
Keyword(s):  
Sign Language ◽  
Recognition System ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Indian Sign Language

STATIC DEVNAGARI SIGN LANGUAGE RECOGNITION

2016 ◽  
Vol 3 (3) ◽  
pp. 13
Author(s):  
VERMA VERSHA ◽  
PATIL SANDEEP B. ◽  
◽  
Keyword(s):  
Sign Language ◽  
Language Recognition ◽  
Sign Language Recognition
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