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IJSTR >> Volume 9 - Issue 1, January 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616


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Md. Buran Basha, S. Ravi Teja, K. Pavan Kumar, M.V.S.D. Anudeep



Convolutional Neural Network, Human computer interaction, Gesture recognition, Deep learning, Hand gesture



Hand gesture recognition is the method by which an individual involving only hands understands specific forms of shape and movement. There are many applications where it is possible to apply hand gesture recognition to enhance control, usability, interaction and training. Communication through hand gesture has been shown successful results for humans and active research continues to replicate the same performance in computer vision systems. Interaction between humans and computers can be significantly enhanced by developments in systems capable of recognizing different hand movements. In this paper we have considered leapGestRecog data set which consists of 1000 images of 10 different members and each of them constituting 9 different labels of hand i.e palm, fist, thumb, index, ok, c, down, palm moved, fist moved. We are using convolutional neural networks which provide a very good result when dealing with images. This hand gesture recognition can be widely in case of physically impaired people and video games which involve gestures to move or play. Now-a- days by showing some gestures we can open some applications in mobile phone. The main goal of hand poses detection is to detect the gesture and able to control it.



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