This paper presents a real-time hand gesture recognizer based on a color glove. The recognizer is formed by three modules. The first module, fed by the frame acquired by a webcam, identifies the hand image in the scene. The second module, a feature extractor, represents the image by a nine-dimensional feature vector. The third module, the classifier, is performed by means of Learning Vector Quantization. The recognizer, tested on a dataset of 907 hand gestures, has shown very high recognition rate.

Real-Time Hand Gesture Recognition Using a Color Glove.

CAMASTRA, Francesco
2011

Abstract

This paper presents a real-time hand gesture recognizer based on a color glove. The recognizer is formed by three modules. The first module, fed by the frame acquired by a webcam, identifies the hand image in the scene. The second module, a feature extractor, represents the image by a nine-dimensional feature vector. The third module, the classifier, is performed by means of Learning Vector Quantization. The recognizer, tested on a dataset of 907 hand gestures, has shown very high recognition rate.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/25252
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