Hand gesture system recognition has received great attention in the current few years because of its ability as it is very important for developing an attractive alternative through human computer interaction modalities. However a more natural form of communication system would make the interaction easier, even the performance would increase and additional cost for hardware would also decrease in fact we might not need extra hardware as well. Thus one of the steps towards the goal of achieving such natural form of communication is Dynamic Gesture Recognition. In dynamic gesture recognition we consider the hand as our only interest of object and our primary focus is on the motion of this object. Therefore here dynamic gesture means the gesture made by a moving hand. In this paper a survey of various hand gesture recognition systems is perceived. There are so many numbers of devices that have been invented, each bringing with it a new aspect of interaction. This paper presents the review of ongoing research on various techniques for determining hand gesture recognition.

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11. C. Keskin, A. Erkan, L. Akarun, "Real time hand tracking and 3D gesture recognition for interactive interfaces using HMM", IEEE Transaction.
12. Harshith. C 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.
13. Malvika Bansal et al. , Gestuelle, "A System to Recognize Dynamic Hand Gestures using Hidden Markov Model to Control Windows Applications", International Journal of Computer Applications (0975 – 8887) Volume 62– No. 17, January 2013.
14. Min et al. , Han gesture recognition using Hidden Markov Model ,International Journal of Artificial Intelligence & Applications (IJAIA), 2012.
15. M. M. Gharasuie et al. , "Real-time Dynamic Hand Gesture Recognition using Hidden Markov Models" , 8th Iranian Conference on Machine Vision and Image Processing (MVIP), 2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP), 978-1-4673-6184-2/13/$31. 00 ©2013 IEEE.
16. Qiu-yu Zhang et al. , "Hand Gesture Contour Tracking Based on Skin Color Probability and State Estimation Model", JOURNAL OF MULTIMEDIA, VOL. 4, NO. 6, DECEMBER 2009.
17. Rafiqul Zaman Khan et al. , Geometric feature extraction for hand gesture recognition, IJCET, Volume 5, Issue 7, July (2014), ISSN 0976 – 6367, pp. 132-141.
18. Rafiqul Zaman Khan et al. , "Hand Gesture Recognition: A Literature Review", IJAIA, Vol. 3, No. 4, July 2012.

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