A Comparison of Hardware Based Approaches for Sign Language Gesture Recognition Systems

Sign language is a gesture-based language used worldwide by the deaf people to communicate with one another. This language comprises of different hand movements and facial expressions. Over the years, different tools and applications have been built and developed by the researchers to facilitate the deaf community in their communication with normal people. One branch of research deals with the recognition of gestures by machines, i.e. the machine is able to understand the gesture performed by a person. Many different approaches involving a variety of hardware including gloves, Microsoft Kinect, and sensors have been used for this purpose. The literature survey reveals that the most significant and advanced work in this regard has been accomplished in American Sign Language (ASL). Whereas, recently noticeable research is being conducted for the development of different Asian sign languages as well. This work presents a study of hardware-based approaches for gesture recognition in ASL and Asian sign languages.

[1]  Tan Tian Swee,et al.  Wireless data gloves Malay sign language recognition system , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[2]  Ahmad Zaki Shukor,et al.  A New Data Glove Approach for Malaysian Sign Language Detection , 2015 .

[3]  Priyanka M. Lokhande,et al.  Data Gloves for Sign Language Recognition System , 2015 .

[4]  Anant Agarwal,et al.  Sign language recognition using Microsoft Kinect , 2013, 2013 Sixth International Conference on Contemporary Computing (IC3).

[5]  Frank Weichert,et al.  Analysis of the Accuracy and Robustness of the Leap Motion Controller , 2013, Sensors.

[6]  Boon Giin Lee,et al.  Smart Wearable Hand Device for Sign Language Interpretation System With Sensors Fusion , 2018, IEEE Sensors Journal.

[7]  Ming C. Leu,et al.  Recognition of Finger Spelling of American Sign Language with Artificial Neural Network Using Position/Orientation Sensors and Data Glove , 2005, ISNN.

[8]  Huaping Liu,et al.  Gesture recognition using data glove: An extreme learning machine method , 2016, 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[9]  Lina El Khansa,et al.  ASL Fingerspelling Translator Glove , 2012 .

[10]  Zhengyou Zhang,et al.  Microsoft Kinect Sensor and Its Effect , 2012, IEEE Multim..

[11]  Paolo Dario,et al.  A Survey of Glove-Based Systems and Their Applications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  Nikhita Praveen,et al.  Sign language interpreter using a smart glove , 2014, 2014 International Conference on Advances in Electronics Computers and Communications.

[13]  Roozbeh Jafari,et al.  Real-time American Sign Language Recognition using wrist-worn motion and surface EMG sensors , 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

[14]  Thad Starner,et al.  American sign language recognition with the kinect , 2011, ICMI '11.

[15]  Kongqiao Wang,et al.  A Sign-Component-Based Framework for Chinese Sign Language Recognition Using Accelerometer and sEMG Data , 2012, IEEE Transactions on Biomedical Engineering.

[16]  Mohamed Mohandes,et al.  Recognition of Two-Handed Arabic Signs Using the CyberGlove , 2013 .

[17]  Zahid Halim,et al.  A Kinect-Based Sign Language Hand Gesture Recognition System for Hearing- and Speech-Impaired: A Pilot Study of Pakistani Sign Language , 2015, Assistive technology : the official journal of RESNA.

[18]  Mayank Singhal,et al.  Smart glove for Sign Language communications , 2016, 2016 International Conference on Accessibility to Digital World (ICADW).

[19]  R. Harikrishnan,et al.  A vision based dynamic gesture recognition of Indian Sign Language on Kinect based depth images , 2013, 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA).

[20]  Syed Atif Mehdi,et al.  Sign language recognition using sensor gloves , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[21]  Nicolas Pugeault,et al.  Spelling it out: Real-time ASL fingerspelling recognition , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[22]  Changsheng Xu,et al.  Discriminative Exemplar Coding for Sign Language Recognition With Kinect , 2013, IEEE Transactions on Cybernetics.

[23]  Hee-Deok Yang,et al.  Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields , 2014, Sensors.

[24]  Wang Jingqiu,et al.  An ARM-based embedded gesture recognition system using a data glove , 2014, The 26th Chinese Control and Decision Conference (2014 CCDC).

[25]  Guang Li,et al.  Sign Language Recognition and Translation with Kinect , 2013 .

[26]  Wen Gao,et al.  A continuous Chinese sign language recognition system , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).