Visual Based Hand Gesture Recognition Systems

Abstract:

This paper describes the techniques used in visual based hand gesture recognition systems. The study is discussed from three aspects: the two categories, the five components, and the methods of feature extraction of visual based hand gesture recognition systems. The two categories are 3D model based systems and appearance model based systems. The five components are image sequences capture, pre-processing, hand regions detection, feature extraction and gesture classification. The methods of feature extraction are Hidden Markov Model (HMM), Artificial Neural Networks (ANN), and Support Vector Machines (SVM). The main ideas of each technique are described in detail.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2422-2425
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2422
• Online since: December 2012
• Authors: Ling Hua Li, Ji Fang Du
• Keywords: Feature Extraction, Hand Gesture Recognition, Visual Based

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