A decomposition approach for complex gesture recognition using DTW and prefix tree

Hui Chen; Tarig Ballal; Tareq Al-Naffouri

doi:10.1109/VR.2019.8797868

A decomposition approach for complex gesture recognition using DTW and prefix tree

Hui Chen
, Tarig Ballal
, Tareq Al-Naffouri

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Gestures are effective tools for expressing emotions and conveying information to the environment. Sequence matching and machine-learning based algorithm are two main methods to recognize continuous gestures. Machine-learning based recognition systems are not flexible to new gestures because the models have to be trained again. On the other hand, the computational time that matching methods required increases with the complexity and the class of the gestures. In this work, we propose a decomposition approach for complex gesture recognition utilizing DTW and prefix tree. This system can recognize 100 gestures with an accuracy of 97.38%.

Original language	English
Title of host publication	26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	876-877
Number of pages	2
ISBN (Electronic)	9781728113777
DOIs	https://doi.org/10.1109/VR.2019.8797868
State	Published - Mar 2019
Externally published	Yes

Publication series

Name	26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Dtw
Gesture recognition
Human
Interaction
Machine
Prefix tree
Time sequence

ASJC Scopus subject areas

Human-Computer Interaction
Media Technology

Access to Document

10.1109/VR.2019.8797868

Cite this

Chen, H., Ballal, T., & Al-Naffouri, T. (2019). A decomposition approach for complex gesture recognition using DTW and prefix tree. In 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings (pp. 876-877). Article 8797868 (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VR.2019.8797868

Chen, Hui ; Ballal, Tarig ; Al-Naffouri, Tareq. / A decomposition approach for complex gesture recognition using DTW and prefix tree. 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 876-877 (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings).

@inproceedings{554cec69e3764665aaa136839f01cf61,

title = "A decomposition approach for complex gesture recognition using DTW and prefix tree",

abstract = "Gestures are effective tools for expressing emotions and conveying information to the environment. Sequence matching and machine-learning based algorithm are two main methods to recognize continuous gestures. Machine-learning based recognition systems are not flexible to new gestures because the models have to be trained again. On the other hand, the computational time that matching methods required increases with the complexity and the class of the gestures. In this work, we propose a decomposition approach for complex gesture recognition utilizing DTW and prefix tree. This system can recognize 100 gestures with an accuracy of 97.38\%.",

keywords = "Dtw, Gesture recognition, Human, Interaction, Machine, Prefix tree, Time sequence",

author = "Hui Chen and Tarig Ballal and Tareq Al-Naffouri",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.",

year = "2019",

month = mar,

doi = "10.1109/VR.2019.8797868",

language = "English",

series = "26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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}

Chen, H, Ballal, T & Al-Naffouri, T 2019, A decomposition approach for complex gesture recognition using DTW and prefix tree. in 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings., 8797868, 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 876-877. https://doi.org/10.1109/VR.2019.8797868

A decomposition approach for complex gesture recognition using DTW and prefix tree. / Chen, Hui; Ballal, Tarig; Al-Naffouri, Tareq.
26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 876-877 8797868 (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A decomposition approach for complex gesture recognition using DTW and prefix tree

AU - Chen, Hui

AU - Ballal, Tarig

AU - Al-Naffouri, Tareq

PY - 2019/3

Y1 - 2019/3

N2 - Gestures are effective tools for expressing emotions and conveying information to the environment. Sequence matching and machine-learning based algorithm are two main methods to recognize continuous gestures. Machine-learning based recognition systems are not flexible to new gestures because the models have to be trained again. On the other hand, the computational time that matching methods required increases with the complexity and the class of the gestures. In this work, we propose a decomposition approach for complex gesture recognition utilizing DTW and prefix tree. This system can recognize 100 gestures with an accuracy of 97.38%.

AB - Gestures are effective tools for expressing emotions and conveying information to the environment. Sequence matching and machine-learning based algorithm are two main methods to recognize continuous gestures. Machine-learning based recognition systems are not flexible to new gestures because the models have to be trained again. On the other hand, the computational time that matching methods required increases with the complexity and the class of the gestures. In this work, we propose a decomposition approach for complex gesture recognition utilizing DTW and prefix tree. This system can recognize 100 gestures with an accuracy of 97.38%.

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KW - Gesture recognition

KW - Human

KW - Interaction

KW - Machine

KW - Prefix tree

KW - Time sequence

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U2 - 10.1109/VR.2019.8797868

DO - 10.1109/VR.2019.8797868

M3 - Conference contribution

AN - SCOPUS:85071838231

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PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Chen H, Ballal T, Al-Naffouri T. A decomposition approach for complex gesture recognition using DTW and prefix tree. In 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 876-877. 8797868. (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings). doi: 10.1109/VR.2019.8797868

A decomposition approach for complex gesture recognition using DTW and prefix tree

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this