Hand gesture authentication using depth camera

Jinghao Zhao; Jiro Tanaka

doi:10.1007/978-3-030-03405-4_45

Hand gesture authentication using depth camera

Jinghao Zhao^*, Jiro Tanaka

^*Corresponding author for this work

Graduate School of Information, Production and Systems

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

5 Citations (Scopus)

Abstract

Nowadays humans are concerned more about their privacy because traditional text password becomes weaker to defend from various attacks. Meanwhile, somatosensory become popular, which makes gesture authentication become possible. This research tries to use humans dynamic hand gesture to make an authentication system, which should have low limitation and be natural. In this paper, we describe a depth camera based dynamic hand gesture authentication method, and generate a template updating mechanism for the system. In the case of simple gesture, the average accuracy is 91.38%, and in the case of complicated gesture, the average accuracy is 95.21%, with 1.65% false acceptance rate. We have also evaluated the system with template updated mechanism.

Original language	English
Title of host publication	Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2
Editors	Rahul Bhatia, Supriya Kapoor, Kohei Arai
Publisher	Springer Verlag
Pages	641-654
Number of pages	14
ISBN (Print)	9783030034047
DOIs	https://doi.org/10.1007/978-3-030-03405-4_45
Publication status	Published - 2019
Event	Future of Information and Communication Conference, FICC 2018 - Singapore, Singapore Duration: 2018 Apr 5 → 2018 Apr 6

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	887
ISSN (Print)	2194-5357

Other

Other	Future of Information and Communication Conference, FICC 2018
Country/Territory	Singapore
City	Singapore
Period	18/4/5 → 18/4/6

Keywords

Depth camera
Gesture authentication
Three-dimensional hand gesture

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science(all)

Access to Document

10.1007/978-3-030-03405-4_45

Cite this

Zhao, J., & Tanaka, J. (2019). Hand gesture authentication using depth camera. In R. Bhatia, S. Kapoor, & K. Arai (Eds.), Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2 (pp. 641-654). (Advances in Intelligent Systems and Computing; Vol. 887). Springer Verlag. https://doi.org/10.1007/978-3-030-03405-4_45

Hand gesture authentication using depth camera. / Zhao, Jinghao; Tanaka, Jiro.
Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. ed. / Rahul Bhatia; Supriya Kapoor; Kohei Arai. Springer Verlag, 2019. p. 641-654 (Advances in Intelligent Systems and Computing; Vol. 887).

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

Zhao, J & Tanaka, J 2019, Hand gesture authentication using depth camera. in R Bhatia, S Kapoor & K Arai (eds), Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. Advances in Intelligent Systems and Computing, vol. 887, Springer Verlag, pp. 641-654, Future of Information and Communication Conference, FICC 2018, Singapore, Singapore, 18/4/5. https://doi.org/10.1007/978-3-030-03405-4_45

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abstract = "Nowadays humans are concerned more about their privacy because traditional text password becomes weaker to defend from various attacks. Meanwhile, somatosensory become popular, which makes gesture authentication become possible. This research tries to use humans dynamic hand gesture to make an authentication system, which should have low limitation and be natural. In this paper, we describe a depth camera based dynamic hand gesture authentication method, and generate a template updating mechanism for the system. In the case of simple gesture, the average accuracy is 91.38%, and in the case of complicated gesture, the average accuracy is 95.21%, with 1.65% false acceptance rate. We have also evaluated the system with template updated mechanism.",

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AB - Nowadays humans are concerned more about their privacy because traditional text password becomes weaker to defend from various attacks. Meanwhile, somatosensory become popular, which makes gesture authentication become possible. This research tries to use humans dynamic hand gesture to make an authentication system, which should have low limitation and be natural. In this paper, we describe a depth camera based dynamic hand gesture authentication method, and generate a template updating mechanism for the system. In the case of simple gesture, the average accuracy is 91.38%, and in the case of complicated gesture, the average accuracy is 95.21%, with 1.65% false acceptance rate. We have also evaluated the system with template updated mechanism.

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Hand gesture authentication using depth camera

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