research-article

A Gesture Interaction System Based on Improved Finger Feature and WE-KNN

Authors:

Hailiang Xiong,

Min ChenAuthors Info & Claims

ICMAI '19: Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence

Pages 39 - 43

https://doi.org/10.1145/3325730.3325759

Published: 12 April 2019 Publication History

Abstract

In most gesture recognition research fields, feature extraction is based on single finger. In this paper, we propose an improved finger feature extraction algorithm based on double fingers, and it is easier to judge the projected distance and angle of five fingertips and can be better applied to gesture recognition with multi-fingers' information. Furthermore, K-nearest neighbor (KNN) classifier based on entropy-weight allocation (WE-KNN) is proposed to improve the accuracy of gesture recognition. Compared with traditional algorithms, the proposed finger feature extraction algorithm combined with WE-KNN can enhance the accuracy of gesture recognition on Leap Motion dataset. What's more, we apply the proposed algorithms to the gesture interaction system of virtual gym scenario, which can increase the interactive fun and improve the interactive experience.

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Cited By

Čopič Pucihar KMeneghello FSalami DSluÿters AVatavu R(2024)Beyond Radar Waves: The First Workshop on Radar-Based Human-Computer InteractionCompanion Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3660515.3662836(97-102)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3660515.3662836
Sluÿters ALambot SVanderdonckt JVillarreal-Narvaez S(2024)Analysis of User-Defined Radar-Based Hand Gestures Sensed Through Multiple MaterialsIEEE Access10.1109/ACCESS.2024.336666712(27895-27917)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3366667
Chioccarello SSluÿters ATestolin AVanderdonckt JLambot S(2023)FORTE: Few Samples for Recognizing Hand Gestures with a Smartphone-attached RadarProceedings of the ACM on Human-Computer Interaction10.1145/35932317:EICS(1-25)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3593231
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Index Terms

A Gesture Interaction System Based on Improved Finger Feature and WE-KNN
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction techniques
      1. Gestural input

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ICMAI '19: Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence

April 2019

232 pages

ISBN:9781450362580

DOI:10.1145/3325730

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Southwest Jiaotong University
Xihua University: Xihua University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 April 2019

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Funding Sources

National Natural Science Foundation of China
National Key Research and Development Program of China
Key Research and Development Program of Shandong Province of China
Natural Science Foundation of Shandong Province of China

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ICMAI 2019

ICMAI 2019: 2019 4th International Conference on Mathematics and Artificial Intelligence

April 12 - 15, 2019

Chegndu, China

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Cited By

Čopič Pucihar KMeneghello FSalami DSluÿters AVatavu R(2024)Beyond Radar Waves: The First Workshop on Radar-Based Human-Computer InteractionCompanion Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3660515.3662836(97-102)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3660515.3662836
Sluÿters ALambot SVanderdonckt JVillarreal-Narvaez S(2024)Analysis of User-Defined Radar-Based Hand Gestures Sensed Through Multiple MaterialsIEEE Access10.1109/ACCESS.2024.336666712(27895-27917)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3366667
Chioccarello SSluÿters ATestolin AVanderdonckt JLambot S(2023)FORTE: Few Samples for Recognizing Hand Gestures with a Smartphone-attached RadarProceedings of the ACM on Human-Computer Interaction10.1145/35932317:EICS(1-25)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3593231
Sluÿters ALambot SVanderdonckt JVatavu R(2023)RadarSense: Accurate Recognition of Mid-air Hand Gestures with Radar Sensing and Few Training ExamplesACM Transactions on Interactive Intelligent Systems10.1145/358964513:3(1-45)Online publication date: 11-Sep-2023
https://dl.acm.org/doi/10.1145/3589645
Sharif HEslaminia AChembrammel PKesavadas T(2022)Classification of Activities of Daily Living Based on Grasp Dynamics Obtained from a Leap Motion ControllerSensors10.3390/s2221827322:21(8273)Online publication date: 28-Oct-2022
https://doi.org/10.3390/s22218273
Sluÿters AOusmer MRoselli PVanderdonckt J(2022)QuantumLeap, a Framework for Engineering Gestural User Interfaces based on the Leap Motion ControllerProceedings of the ACM on Human-Computer Interaction10.1145/35322116:EICS(1-47)Online publication date: 17-Jun-2022
https://dl.acm.org/doi/10.1145/3532211
Sluÿters ALambot SVanderdonckt J(2022)Hand Gesture Recognition for an Off-the-Shelf Radar by Electromagnetic Modeling and InversionProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511107(506-522)Online publication date: 22-Mar-2022
https://dl.acm.org/doi/10.1145/3490099.3511107
Hu ZSun SWu YYan HZhu T(2021)Research on Gesture Recognition and Interaction of Virtual Collaborative Disassembly Training2021 IEEE 7th International Conference on Virtual Reality (ICVR)10.1109/ICVR51878.2021.9483870(246-253)Online publication date: 20-May-2021
https://doi.org/10.1109/ICVR51878.2021.9483870
Nogales RBenalcázar M(2020)Real-Time Hand Gesture Recognition Using KNN-DTW and Leap Motion ControllerInformation and Communication Technologies10.1007/978-3-030-62833-8_8(91-103)Online publication date: 11-Nov-2020
https://doi.org/10.1007/978-3-030-62833-8_8

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