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A novel approach to extract hand gesture feature in depth images

Research output: Contribution to journalArticlepeer-review

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A novel approach to extract hand gesture feature in depth images. / Ju, Zhaojie; Gao, Dongxu; Cao, Jiangtao; Liu, Honghai.

In: Multimedia Tools and Applications, Vol. 75, No. 19, 10.2016, p. 11929-11943.

Research output: Contribution to journalArticlepeer-review

Harvard

Ju, Z, Gao, D, Cao, J & Liu, H 2016, 'A novel approach to extract hand gesture feature in depth images', Multimedia Tools and Applications, vol. 75, no. 19, pp. 11929-11943. https://doi.org/10.1007/s11042-015-2609-2

APA

Ju, Z., Gao, D., Cao, J., & Liu, H. (2016). A novel approach to extract hand gesture feature in depth images. Multimedia Tools and Applications, 75(19), 11929-11943. https://doi.org/10.1007/s11042-015-2609-2

Vancouver

Ju Z, Gao D, Cao J, Liu H. A novel approach to extract hand gesture feature in depth images. Multimedia Tools and Applications. 2016 Oct;75(19):11929-11943. https://doi.org/10.1007/s11042-015-2609-2

Author

Ju, Zhaojie ; Gao, Dongxu ; Cao, Jiangtao ; Liu, Honghai. / A novel approach to extract hand gesture feature in depth images. In: Multimedia Tools and Applications. 2016 ; Vol. 75, No. 19. pp. 11929-11943.

Bibtex

@article{45cee9af608e4d7a8d1dc1fef46240ae,
title = "A novel approach to extract hand gesture feature in depth images",
abstract = "This paper proposes a novel approach to extract human hand gesture features in real-time from RGB-D images based on the earth mover{\textquoteright}s distance and Lasso algorithms. Firstly, hand gestures with hand edge contour are segmented using a contour length information based de-noise method. A modified finger earth mover{\textquoteright}s distance algorithm is then applied applied to locate the palm image and extract fingertip features. Lastly and more importantly, a Lasso algorithm is proposed to effectively and efficiently extract the fingertip feature from a hand contour curve. Experimental results are discussed to demonstrate the effectiveness of the proposed approach.",
keywords = "RCUK, EPRC, EP/G041377/1",
author = "Zhaojie Ju and Dongxu Gao and Jiangtao Cao and Honghai Liu",
year = "2016",
month = oct,
doi = "10.1007/s11042-015-2609-2",
language = "English",
volume = "75",
pages = "11929--11943",
journal = "Multimedia Tools and Applications",
issn = "1380-7501",
publisher = "Springer Netherlands",
number = "19",

}

RIS

TY - JOUR

T1 - A novel approach to extract hand gesture feature in depth images

AU - Ju, Zhaojie

AU - Gao, Dongxu

AU - Cao, Jiangtao

AU - Liu, Honghai

PY - 2016/10

Y1 - 2016/10

N2 - This paper proposes a novel approach to extract human hand gesture features in real-time from RGB-D images based on the earth mover’s distance and Lasso algorithms. Firstly, hand gestures with hand edge contour are segmented using a contour length information based de-noise method. A modified finger earth mover’s distance algorithm is then applied applied to locate the palm image and extract fingertip features. Lastly and more importantly, a Lasso algorithm is proposed to effectively and efficiently extract the fingertip feature from a hand contour curve. Experimental results are discussed to demonstrate the effectiveness of the proposed approach.

AB - This paper proposes a novel approach to extract human hand gesture features in real-time from RGB-D images based on the earth mover’s distance and Lasso algorithms. Firstly, hand gestures with hand edge contour are segmented using a contour length information based de-noise method. A modified finger earth mover’s distance algorithm is then applied applied to locate the palm image and extract fingertip features. Lastly and more importantly, a Lasso algorithm is proposed to effectively and efficiently extract the fingertip feature from a hand contour curve. Experimental results are discussed to demonstrate the effectiveness of the proposed approach.

KW - RCUK

KW - EPRC

KW - EP/G041377/1

U2 - 10.1007/s11042-015-2609-2

DO - 10.1007/s11042-015-2609-2

M3 - Article

VL - 75

SP - 11929

EP - 11943

JO - Multimedia Tools and Applications

JF - Multimedia Tools and Applications

SN - 1380-7501

IS - 19

ER -

ID: 2972905