NDLI: Dynamic hand gesture classification based on radar micro-Doppler signatures

Content Provider	Semantic Scholar
Author	Zhang, Shimeng Li, Gang Ritchie, Matthew Fioranelli, Francesco Griffiths, Hugh D.
Copyright Year	2016
Abstract	Dynamic hand gesture recognition is of great importance for human-computer interaction. In this paper, we present a method to discriminate the four kinds of dynamic hand gestures, snapping fingers, flipping fingers, hand rotation and calling, using a radar micro-Doppler sensor. Two micro-Doppler features are extracted from the time-frequency spectrum and the support vector machine is used to classify these four kinds of gestures. The experimental results on measured data demonstrate that the proposed method can produce a classification accuracy higher than 88.56%.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF HTM / HTML
DOI	10.1109/RADAR.2016.8059518
Alternate Webpage(s)	http://eprints.gla.ac.uk/150350/1/150350.pdf
Journal	2016 CIE International Conference on Radar (RADAR)
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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