Neural Network based Classifying Static Hand Gesture Recognition

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Vaishali M. Gulhane
Madhavi S. Joshi, Manik D. Ingole


Considerable effort has been put towards developing intelligent and natural interfaces between users and computer systems. This is done by means of a variety of modes of information (visual, audio, pen, etc.). The use of gestures as means to convey information is an important part of human communication. The automatic recognition of gestures enriches Human–Computer Interaction by offering a natural and intuitive method of data input. This paper presents a new technique for hand gesture recognition, for the Human-Computer Interaction (HCI) based on shape analysis. The objective of this effort was to explore the utility of a neural network-based approach to the recognition of the hand gestures. A neural network is build for the classification by using back-propagation learning algorithm. The overall model is designed to be a simple gestural interface prototype for various PC applications.


Keywords: Mouse replacement, American Sign Language, Artificial Neural Network, Gesture modeling.


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