Single Person Hand Gesture Recognition using Artificial Neural Network

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The introduction of gesture recognition has led to a better man-machine interaction (MMI). Gesture recognition is an interesting topic in computer vision and pattern recognition (CVPR) technology which deals with the mathematical interpretation of human gestures via a computing device. It enables a human being to interact with machines without any mechanical contact. Hand gesture recognition has been granted as one of the emerging fields in research today providing a natural way of communication between man and a machine. Gestures are some forms of body motions which a person expresses when doing work or giving a reply. Human body tracking is a well-studied topic in today’s era of man-machine interaction and it can be formed by the virtue of human skeleton structures. These skeleton structures have been detected successfully due to the smart progress of some devices, used to measure depth (e.g. Sony PlayStation, Kinect sensor, etc.). Human body movements have been viewed using these depth sensors which can provide sufficient accuracy while tracking full body in real-time mode with low cost.


Biswarup Ganguly


Biswarup Ganguly is currently working as an Assistant Professor with the Electrical Engineering Department, Meghnad Saha Institute of Technology, Kolkata, India. His current research interests include the condition monitoring of electrical and biomedical systems and applications of vision-based measurement systems.

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LAP LAMBERT Academic Publishing


artificial neural network, Gesture Recognition, Kinect sensor, Man-Machine-Interaction, Artificial Intelligence

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TECHNOLOGY / Electronics / General