Abstract
This paper presents a real-time hand gesture recognizer based on a Learning Vector Quantization (LVQ) classifier. The recognizer is formed by two modules. The first module, mainly composed of a data glove, performs the feature extraction. The second module, the classifier, is performed by means of LVQ. The recognizer, tested on a dataset of 3900 hand gestures, performed by people of different gender and physique, has shown very high recognition rate.
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Camastra, F., De Felice, D. (2013). LVQ-Based Hand Gesture Recognition Using a Data Glove. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_17
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DOI: https://doi.org/10.1007/978-3-642-35467-0_17
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