DocumentCode :
3411085
Title :
Hand-gesture-based human-machine interface system using Compressive Sensing
Author :
Mantecon, Tomas ; Mantecon, Ana ; del-Blanco, Carlos R. ; Jaureguizar, Fernando ; Garcia, Narciso
Author_Institution :
ETSI Telecomun., Univ. Politec. de Madrid, Madrid, Spain
fYear :
2015
fDate :
24-26 June 2015
Firstpage :
1
Lastpage :
2
Abstract :
A novel and robust vision-based human-machine interface system to naturally interact with computers/smart devices is proposed. The key contribution is the introduction of a Compressive Sensing technique to largely reduce the dimensionality of highly discriminative feature descriptors (computed from depth imagery), which originally have an excessive and inoperative high dimension to be applied to a Support Vector Machine based classifier. The experimental results prove the appropriateness of this approach for the proposed system.
Keywords :
compressed sensing; gesture recognition; human computer interaction; pattern classification; support vector machines; compressive sensing; feature descriptors; hand-gesture-based human-machine interface system; robust vision-based human-machine interface system; smart devices; support vector machine based classifier; Accuracy; Compressed sensing; Consumer electronics; Gesture recognition; Man machine systems; Robustness; Support vector machines; Compressive Sensing; DLQP; LBP; SVM; gesture recognition; human-machine interface;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics (ISCE), 2015 IEEE International Symposium on
Conference_Location :
Madrid
Type :
conf
DOI :
10.1109/ISCE.2015.7177828
Filename :
7177828
Link To Document :
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