research-article

Finger identification and hand gesture recognition techniques for natural user interface

Authors:

Jiro TanakaAuthors Info & Claims

APCHI '13: Proceedings of the 11th Asia Pacific Conference on Computer Human Interaction

Pages 274 - 279

https://doi.org/10.1145/2525194.2525296

Published: 24 September 2013 Publication History

Abstract

The natural user interface using hand gesture have been popular field in Human-Computer-Interaction(HCI). Many research papers have been proposed in this field. They proposed vision-based, glove-based and depth-based approach for hand gesture recognition. However, hand gesture itself is simple and not natural way to interact. In otherwise, hand gesture recognition using finger tracking and identification can be implemented more robust and subtle recognition. Recently, new horizons are open with the development of sensors and technology such as Kinect and Depth-Sense. This development has made possible robust recognition, like finger identification and hand gesture recognition in bad conditions such as dark light and rough background as well. In this paper, we proposed a new finger identification and hand gesture recognition techniques with kinect depth data. Our proposed finger identification and gesture recognition methods provide natural interactions and interface by using fingers. We implemented interfaces and designed hand gestures using this method. This paper explains finger identification method and hand gesture recognition in detail. We show the preliminary experiment for evaluating accuracy of finger identification and hand gesture recognition accuracy. Finally, we discuss the result of evaluation and our contributions.

References

[1]

Z. Ren, J. Meng and Z. Zhang. "Robust Hand Gesture Recognition with Kinect Sensor", MM'11, Proceedings of the 19th ACM international conference on Multimedia, 2011.

Digital Library

[2]

D. Wigdor and D. Wixon. "BRAVE NUI WORLD", Published by Morgan Kaufmann, pp.9--15, 2011.

[3]

Y. Cheoljong, J. Yujeong, B. Jounghoon, H. David and K. Hanseok. "Gesture recognition using depth-based hand tracking for contactless controller application", Consumer Electronics (ICCE), 2012 IEEE International Conference on, pp. 297--298, 2012

[4]

J. Raheja, C. Ankit and S. Singal. "Tracking of fingertips and centers of palm using KINECT", 2011 Third International Conference on Computational Intelligence Modelling Simulation, pp. 248--252, 2011.

Digital Library

[5]

S. Chu and J. Tanaka. "Hand Gesture for Taking Self Portrait", Human-Computer Interaction, Part II, HCII 2011, LNCS 6762, pp. 238--247, 2011.

Digital Library

[6]

H. Kenn, F. Megan and R. Sugar. "A glove-based gesture interface for wearable computing applications", Proceedings of the IFAWC 4th international forum on applied wearable computing 2007, pp. 169--177, 2007.

[7]

Hand and finger tracking with Kinect depth data. http://candescentnui.codeplex.com.

[8]

S. Lenman, L. Bretzner and B. Thuresson. "Computer Vision Based Hand Gesture Inter-faces for Human-Computer Interaction", Technical Report CID-172, Center for User Oriented IT Design, pp.3--4, 2002.

[9]

J. Wachs, M. Kölsch, H. Stern, and Y. Edan. "Vision-based hand-gesture applications", Communications of the ACM, Vol. 54 Issue 2, pp.60--70., 2011.

Digital Library

[10]

V. Frati and D. Prattichizzo. "Using Kinect for hand tracking and rendering in wearable haptics", IEEE World Haptics Conference, pp. 317--321, 2011.

[11]

R. Graham. "An efficient algorithm for determining the convex hull of a finite planar set", Information Processing Letter, pp. 132--133, 1972.

[12]

M. Tang. "Hand Gesture Recognition Using Microsoft's Kinect." Paper written for CS228, Winter 2010. Technologies, UIST'11, ACM, pp.1--9, 2011.

[13]

G. He, S. Kang, W. Song and S. Jung. "Real time gesture recognition using 3D depth camera", Software Engineering and Service Science (ICSESS), 2011 IEEE 2nd International Conference on, pp.187--190. 2011.

[14]

OpenNI organization. OpenNI User- Guide, 2012.

[15]

H. Nanda and K. Fujimura. "Visual tracking using depth data", Conference on Computer Vision and Pattern Recognition Workshop, pp.37, 2004.

Digital Library

[16]

The teardown, Engineering & Technology, Vol.6, no.3, pp. 94--95, 2011.

[17]

D. McNeill. "So you think gestures are nonverbal?", Psychological Review, vol92 (3), pp. 350--373, 1985.

[18]

A. Akl. "A Novel Accelerometer-based Gesture Recognition System", Signal Processing, IEEE Transactions on, University of Toronto, pp. 2--3, 2010.

Digital Library

Cited By

Tao LLiu YZou SZhang ZZhao X(2024)Enhancing Gesture Recognition in Low-Light Conditions Using Laser-Induced Graphene Flexible Strain SensorsIEEE Sensors Journal10.1109/JSEN.2023.334534424:4(5256-5265)Online publication date: 15-Feb-2024
https://doi.org/10.1109/JSEN.2023.3345344
Picard SBotev JNiknam S(2023)A Dynamic and Scriptable Environment and Framework for Stimulus-Based Cognitive Research in Virtual Reality2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct60411.2023.00084(387-392)Online publication date: 16-Oct-2023
https://doi.org/10.1109/ISMAR-Adjunct60411.2023.00084
Sharma VWalia N(2023)Gesture Recognition using Cognitive AI and Deep Learning2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)10.1109/ICAEECI58247.2023.10370816(1-6)Online publication date: 19-Oct-2023
https://doi.org/10.1109/ICAEECI58247.2023.10370816
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Index Terms

Finger identification and hand gesture recognition techniques for natural user interface
1. Human-centered computing

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cover image ACM Conferences

APCHI '13: Proceedings of the 11th Asia Pacific Conference on Computer Human Interaction

September 2013

420 pages

ISBN:9781450322539

DOI:10.1145/2525194

General Chairs:
Sanjay Tripathi
ABB Corporate Research, India
,
Anirudha Joshi
IIT Bombay, India

Copyright © 2013 ACM.

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Published: 24 September 2013

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APCHI '13: 11th Asia Pacific Conference on Computer Human Interaction

September 24 - 27, 2013

Bangalore, India

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Cited By

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https://doi.org/10.1109/JSEN.2023.3345344
Picard SBotev JNiknam S(2023)A Dynamic and Scriptable Environment and Framework for Stimulus-Based Cognitive Research in Virtual Reality2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct60411.2023.00084(387-392)Online publication date: 16-Oct-2023
https://doi.org/10.1109/ISMAR-Adjunct60411.2023.00084
Sharma VWalia N(2023)Gesture Recognition using Cognitive AI and Deep Learning2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)10.1109/ICAEECI58247.2023.10370816(1-6)Online publication date: 19-Oct-2023
https://doi.org/10.1109/ICAEECI58247.2023.10370816
Bhushan SAlshehri MKeshta IChakraverti ARajpurohit JAbugabah A(2022)An Experimental Analysis of Various Machine Learning Algorithms for Hand Gesture RecognitionElectronics10.3390/electronics1106096811:6(968)Online publication date: 21-Mar-2022
https://doi.org/10.3390/electronics11060968
Hirsch LLi JMayer SButz A(2022)A Survey of Natural Design for InteractionProceedings of Mensch und Computer 202210.1145/3543758.3543773(240-254)Online publication date: 4-Sep-2022
https://dl.acm.org/doi/10.1145/3543758.3543773
Vijeya Kaveri VMeenakshi VMeena Devi RKousalya ASujaritha M(2022)Object Tracking GloveMaterials Today: Proceedings10.1016/j.matpr.2021.12.27951(2525-2529)Online publication date: 2022
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Sahana TBasu SNasipuri MMollah A(2022)MRCS: multi-radii circular signature based feature descriptor for hand gesture recognitionMultimedia Tools and Applications10.1007/s11042-021-11743-w81:6(8539-8560)Online publication date: 1-Mar-2022
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Tan JShao LLam NToomey AGe L(2021)Intelligent textiles: designing a gesture-controlled illuminated textile based on computer visionTextile Research Journal10.1177/0040517521103424592:17-18(3034-3048)Online publication date: 13-Aug-2021
https://doi.org/10.1177/00405175211034245
Juneja SJuneja ADhiman GJain SDhankhar AKautish S(2021)Computer Vision-Enabled Character Recognition of Hand Gestures for Patients with Hearing and Speaking DisabilityMobile Information Systems10.1155/2021/49124862021Online publication date: 14-Dec-2021
https://dl.acm.org/doi/10.1155/2021/4912486
Kim YReza MMcGrenere JYoon DKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Designers Characterize Naturalness in Voice User Interfaces: Their Goals, Practices, and ChallengesProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445579(1-13)Online publication date: 6-May-2021
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