Pakistan Sign Language Recognition Using Statistical Template Matching
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Pakistan Sign Language Recognition Using Statistical Template Matching

Authors: Aleem Khalid Alvi, M. Yousuf Bin Azhar, Mehmood Usman, Suleman Mumtaz, Sameer Rafiq, RaziUr Rehman, Israr Ahmed

Abstract:

Sign language recognition has been a topic of research since the first data glove was developed. Many researchers have attempted to recognize sign language through various techniques. However none of them have ventured into the area of Pakistan Sign Language (PSL). The Boltay Haath project aims at recognizing PSL gestures using Statistical Template Matching. The primary input device is the DataGlove5 developed by 5DT. Alternative approaches use camera-based recognition which, being sensitive to environmental changes are not always a good choice.This paper explains the use of Statistical Template Matching for gesture recognition in Boltay Haath. The system recognizes one handed alphabet signs from PSL.

Keywords: Gesture Recognition, Pakistan Sign Language, DataGlove, Human Computer Interaction, Template Matching, BoltayHaath

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084442

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[1] Dr. Nasir Sulman, Sadaf Zuberi, "Pakistan Sign Language - A Synopsis", Pakistan., June 2000.
[2] I. Wachsmuth, T. Sowa (Eds.), "Towards an Automatic Sign Language Recognition System Using Subunits", London, April 2001, pp. 1-2
[3] Waleed Kadous, "GRASP: Recognition of Australian sign language using Instrumented gloves", http://www.cse.unsw.edu.au/~waleed/thesis/thesis.html, Australia, October 1995,pp. 1-2.
[4] Andrea Corradini, Horst-Michael Gross. 2000, "Camera-based Gesture Recognition for Robot Control",2000 IEEE 133-138.
[5] Andrea Corradini ,Horst-Michael Gross. 2000, "A Hybrid Stochastic- Connectionist Architecture for Gesture Reognition",2000 IEEE 336- 341.
[6] Vesa-Matti Mantyla, Jani Mantyjarvi, Tapio Seppanen, Esa tuulari. 2000, "Hand Gesture Recognition of a mobile device user",2000 IEEE 281-284.
[7] Sim Oni, "Gesture Recognition Using Neural Network", Taiwan, 2000, pp. 1-2.
[8] Richard Watson, "A survey of Gesture Recognition Techniques Technical Report", Trinity College, Dublin, July 1993, pp. 6
[9] The Webopedia Website, www.webopaedia.com
[10] Aleksander, I. and Morton, H., An Introduction to Neural Computing, Chapman & Hall, London, 1990. Amari, S. I., "Learning patterns and pattern sequences by self-organizing nets," IEEE Trans. Comput., vol. 21, pp. 1197-1206, 1972.
[11] Dictionary Dot Com, http://www.dictionary.com/
[12] Dictionary Dot Com reference, http://dictionary.reference.com/
[13] Barbara Liskov , Program development in java, pg. 356,chap 11
[14] Ian Sommerville, Software Engineering, pg. 8, chap 1
[15] The 5DT Website, www.5dt.com
[16] Dictionary Online, http://dictionary.reference.com
[17] S. Sidney Fels. Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks -- An Approach to Building Adaptive Interfaces. PhD thesis, Computer Science Department, University of Toronto, 1994., pp 35-42
[18] Murakami and Taguchi, Gesture recognition using recurrent neural networks. In CHI '91 Conference Proceedings, pages 237--242. Human Interface Laboratory, Fujitsu Laboratories, ACM, 1991.
[19] Peter Vamplew. The SLARTI sign language recognition system: A progress report. University of tasmanis, Australia, Pp. 1-3
[20] Waleed Kadous, "GRASP: RECOGNITION OF AUSTRALIAN SIGN LANGUAGE USING INSTRUMENTED GLOVES ", Australia, OCTOBER 1995 , pp. 1-2, http://www.cse.unsw.edu.au/~waleed/thesis/ thesis.html
[21] K.S. Fu. Syntactic Pattern Recognition, Prentice-Hall 1981, Pp 75-80
[22] K.S. Fu. and T.S. Yu. Statistical pattern Classification using Contextual Information, Recognition and image Processing Series, Research Studies Pres, 1980.
[23] David J, Sturman, Whole hand input, Ph.D. Thesis, MIT, 1992, Pp. 14- 56
[24] Dean Rubine, Automatic Recognition of gestures, PhD, thesis, Carnegie Mellon University , December 1991, Pp. 90-156