Hand Gesture Recognition System using Convolutional Neural Network
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Abstract
Gestures provide the ability to interact with machines efficiently through Human computer interaction; this can be accomplished by creating interfaces which perform gesture recognition, thereby automating tasks. Hand gesture recognition is a type of gesture recognition that is very useful to automate tasks for the specially challenged. Challenges in this area are complex background, camera angle, and illumination. It uses GMM technique for background subtraction and VGG16 architecture, trained on images captured using a camera, to achieve a fast and robust classification system for gesture recognition, as demonstrated by experiments. An F1-score above 92% is obtained for all classes.
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