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Erschienen in: Neural Computing and Applications 3-4/2014

01.09.2014 | Original Article

Hand posture and gesture recognition technology

verfasst von: Haitham Sabah Badi, Sabah Hussein

Erschienen in: Neural Computing and Applications | Ausgabe 3-4/2014

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Abstract

Hand gestures that are performed by one or two hands can be categorized according to their applications into different categories including conversational, controlling, manipulative and communicative gestures. Generally, hand gesture recognition aims to identify specific human gestures and use them to convey information. The process of hand gesture recognition composes mainly of four stages: hand gesture images collection, gesture image preprocessing using some techniques including edge detection, filtering and normalization, capture the main characteristics of the gesture images and the evaluation (or classification) stage where the image is classified to its corresponding gesture class. There are many methods that have been used in the classification stage of hand gesture recognition such as Artificial Neural Networks, template matching, Hidden Markov Models and Dynamic Time Warping. This exploratory survey aims to provide a progress report on hand posture and gesture recognition technology.

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Metadaten
Titel
Hand posture and gesture recognition technology
verfasst von
Haitham Sabah Badi
Sabah Hussein
Publikationsdatum
01.09.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 3-4/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1574-4

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