BoMW: Bag of Manifold Words for One-Shot Learning Gesture Recognition From Kinect

In this paper, we study one-shot learning gesture recognition on RGB-D data recorded from Microsoft's Kinect. To this end, we propose a novel bag of manifold words (BoMW)-based feature representation on symmetric positive definite (SPD) manifolds. In particular, we use covariance matrices to ex...

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Bibliographic Details
Published in:	IEEE transactions on circuits and systems for video technology Vol. 28; no. 10; pp. 2562 - 2573
Main Authors:	Zhang, Lei, Zhang, Shengping, Jiang, Feng, Qi, Yuankai, Zhang, Jun, Guo, Yuliang, Zhou, Huiyu
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Coding covariance descriptor Covariance matrix Encoding Euclidean geometry Euclidean space Feature extraction Gesture recognition Hidden Markov models kernel sparse coding Learning Manifolds Mathematical analysis Matrix methods Representations reproducing kernel Hilbert space Riemannian manifold Shape State of the art Teaching methods Three-dimensional displays Video data
ISSN:	1051-8215, 1558-2205
Online Access:	Get full text
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