Hand gesture recognition using superpixel tracking and RBF classifier
Zhu H.-M.; Pun C.-M.
Source Publication2015 5th International Workshop on Computer Science and Engineering: Information Processing and Control Engineering, WCSE 2015-IPCE
AbstractA hand gesture recognition system using superpixel tracking and radial basis function (RBF) classifier is proposed in this paper. Firstly we employed the motion detection of superpixels and unsupervised image segmentation to detect the target hand in the first few video frames. Then the hand appearance model is constructed from its surrounding superpixels. By incorporating the failure recovery and template matching in the tracking process, the target hand is tracked by the proposed adaptive superpixel based tracking algorithm. Experimental results show that the extracted motion trajectories recognized with a trained RBF classifier can achieve better performance compared to the existing state of the art methods.
KeywordHand detection Motion tracking Superpixel Template matching
URLView the original
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Document TypeConference paper
CollectionUniversity of Macau
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Zhu H.-M.,Pun C.-M.. Hand gesture recognition using superpixel tracking and RBF classifier[C],2015.
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