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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Lamberti, L., Camastra, F. (2011). Real-Time Hand Gesture Recognition Using a Color Glove. In: Maino, G., Foresti, G.L. (eds) Image Analysis and Processing – ICIAP 2011. ICIAP 2011. Lecture Notes in Computer Science, vol 6978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24085-0_38
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DOI: https://doi.org/10.1007/978-3-642-24085-0_38
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