Abstract
The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.
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Liu, J., Kavakli, M. (2010). Hand Gesture Recognition Based on Segmented Singular Value Decomposition. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_22
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DOI: https://doi.org/10.1007/978-3-642-15390-7_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15389-1
Online ISBN: 978-3-642-15390-7
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