Vision-based hand posture detection and recognition for Sign Language—A study
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Date
2011-05-17
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Unlike general gestures, Sign Languages (SLs) are highly structured so that it provides an appealing test bed for understanding more general principles for hand shape, location and motion trajectory. Hand posture shape in other words static gestures detection and recognition is crucial in SLs and plays an important role within the duration of the motion trajectory. Vision-based hand shape recognition can be accomplished using three approaches 3D hand modelling, appearance-based methods and hand shape analysis. In this survey paper, we show that extracting features from hand shape is so essential during recognition stage for applications such as SL translators.
Description
Keywords
Hand detection, Hand posture recognition, Feature extraction
Citation
Bilal, S., Akmeliawati, R., El Salami, M. J., & Shafie, A. A. (2011, May). Vision-based hand posture detection and recognition for Sign Language—A study. In 2011 4th International Conference on Mechatronics (ICOM) (pp. 1-6). IEEE.