Hand Gesture Recognition for Indian Sign Language: A Review

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-21 Number-3
Year of Publication : 2015
Authors : Suruchi Bhatnagar, Suyash Agrawal
DOI :  10.14445/22312803/IJCTT-V21P122

MLA

Suruchi Bhatnagar, Suyash Agrawal "Hand Gesture Recognition for Indian Sign Language: A Review". International Journal of Computer Trends and Technology (IJCTT) V21(3):121-122, March 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Gesture recognition is a technique to analyze the human body movement. It helps humans communicate with machines (HCI) naturally without any mechanical devices. There has been always considered a challenge in the expansion of a natural interaction interface, where people interact with expertise since they are used to cooperate with the real world, this technique is called as Human Computer Interaction (HCI). Here, we are going to have a study on Hand Gesture Recognition. It has really vast area to research where we have select the very interesting topic Indian Sign Language. ISL has got standardised recently, so there is little research work that has happened in this area. In this area we have many developed methods to recognize alphabets and numerals of ISL. There are various approaches for recognition of ISL and we have done a comparative study among Hidden Markov Model (HMM), Naïve Bayes’ Classifier, YUV Colour space and CAMSHIFT Algorithm and Back Propagation Neural Network (BPNN).

References
[1] Deepika Tewari and Sanjay Kumar Srivastava. A Visual Recognition of Static Hand Gestures in Indian Sign Language based on Kohonen Self- Organizing Map Algorithm, International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-2, Issue-2, December 2012.
[2] Jesus Suarez and Robin R. Murphy. Hand Gesture Recognition with Depth Images: A Review, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication. September 9-13, 2012. Paris, France.
[3] H Harshith.C, Karthik.R.Shastry, Manoj Ravindran et al. Survey On Various Gesture Recognition Techniques For Interfacing Machines Based On Ambient Intelligence, International Journal of Computer Science & Engineering Survey (IJCSES) Vol.1, No.2, November 2010.
[4] A. Bosch, A. Zisserman, X. Munozet et al. Scene Classification Using A Hybrid Generative /Discriminative Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 4, pp. 712-727, 2008, 993-1007.
[5] Jagdish Lal Raheja, Umesh Kumar, Human Facial Expression Detection Image Using Back Propagation Neural Network., International Journal of Computer Science and Information Technology (IJCSIT); Vol. 2, No. 1, Feb 2010, pp. 116-112.
[6] Pujan Ziaie et.al, “Using a Naïve Bayes’ Classifier based on KNearest Neighbors with Distance Weighting for Static Hand-Gesture Recognition in a Human-Robot Dialog System”, Advances in Computer Science and Engineering Communications in Computer and Information Science, 2009, Volume 6, Part 1, Part 8, pp. 308-315.
[7] Ankita Saxena, Deepak Kumar Jain, ssAnanya Singhal. Hand Gesture Recognition using an Android Device, 2014 Fourth International Conference on Communication Systems and Network Technologies.

Keywords
Indian Sign Language, Human computer Interaction, Hidden Markov Model, Naïve Bayes’ Classifier, CAMSHIFT algorithm, Back Propagation Neural Network.