Research Article
Infrared dynamic hand gesture recognition based on Gabor feature and sparse representation
@ARTICLE{10.4108/icst.mobimedia.2015.259096, author={Lei Shang and Zhi Liu and Haixia Zhang}, title={Infrared dynamic hand gesture recognition based on Gabor feature and sparse representation}, journal={EAI Endorsed Transactions on Self-Adaptive Systems}, volume={1}, number={4}, publisher={EAI}, journal_a={SAS}, year={2015}, month={8}, keywords={dynamic hand gesture recognition, infrared image, twofold selection, gabor feature, sparse representation classification}, doi={10.4108/icst.mobimedia.2015.259096} }- Lei Shang
Zhi Liu
Haixia Zhang
Year: 2015
Infrared dynamic hand gesture recognition based on Gabor feature and sparse representation
SAS
EAI
DOI: 10.4108/icst.mobimedia.2015.259096
Abstract
Dynamic hand gesture recognition is a subject which has been investigated almost from the beginning of using terminals to interact with the computer central unit. We present a method for dynamic hand gesture recognition with image source acquired by a single IR camera. First of all, the hand images are captured by one infrared camera, which are light independent, and not be limited by skin color. Second, due to the dynamic hand gesture sets contain more than one frame, the data dimension is very large and the adjacent frames have limited difference. We use the twofold selections to choose the key frames from the gesture image sets. The Gabor feature is used to describe the locality variation. And the Sparse representation based classification (SRC) is used for recognition. Experimental results on dynamic hand gesture images with variations of rotation and translation demonstrate the good performance of our method.
Copyright © 2015 Z. Liu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
