Skip to main content
Springer Nature Link
Log in

User identification approach based on simple gestures

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

We present an intuitive, implicit, gesture based identification system suited for applications such as the user login to home multimedia services, with less strict security requirements. The term “implicit gesture” in this work refers to a natural physical hand manipulation of the control device performed by the user, who picks it up from its neutral motionless position or shakes it. For reference with other related systems, explicit and well defined identification gestures were used. Gestures were acquired by an accelerometer sensor equipped device in a form of the Nintendo WiiMote remote controller. A dynamic time warping method is used at the core of our gesture based identification system. To significantly increase the computational efficiency and temporal stability, the “super-gesture” concept was introduced, where acceleration features of multiple gestures are combined in only one super-gesture template per each user. User evaluation spanning over a period of 10 days and including 10 participants was conducted. User evaluation study results show that our algorithm ensures nearly 100 % recognition accuracy when using explicit identification signature gestures and between 88 % and 77 % recognition accuracy when the system needs to distinguish between 5 and 10 users, using the implicit “pick-up” gesture. Performance of the proposed system is comparable to the results of other related works when using explicit identification gestures, while showing that implicit gesture based identification is also possible and viable.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Abate AF, Nappi M, Riccio D, Sabatino G (2007) 2D and 3D face recognition: a survey. Pattern Recognit Lett 28:1885–1906

    Article  Google Scholar 

  2. Cho SJ, Oh JK, Bang WC, Chang W, Choi E, Jing Y, Cho J, Kim DY (2004) Magic wand: A Hand-Drawn Gesture Input Device in 3-D Space with Inertial Sensors. Proceedings of the 9th Int’l Workshop on Frontiers in Handwriting Recognition

  3. Eurostat Average household size, http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=ilc_lvph01&lang=en

  4. Guna J, Stojmenova E, Lugmayr A, Humar I, Pogačnik M (2012) User identification approach based on simple gestures, Proceedings of the 5th International Workshop on Semantic Ambient Media Experience (SAME) - in conjunction with Pervasive 2012 [Elektronski vir] : Newcastle, UK, 18th June 2012/[editors] Artur Lugmayr … [et al.]

  5. Jain AK, Flynn P, Ross AA (2008) Handbook of Biometrics. Springer http://www.springer.com/computer/image+processing/book/978-0-387-71040-2

  6. Jain AK, Ross A, Prabhakar S (2004) An introduction to biometric recognition. IEEE Trans Circ Syst Video Technol 14(1):4–20. doi:10.1109/TCSVT.2003.818349

    Google Scholar 

  7. Jun-qi K, Hui W, Guang-quan, Z (2009) Gesture recognition model based on 3D Accelerations. Proceedings of 2009 4th InternationalConference on Computer Science & Education

  8. Kela J, Korpipää P, Mäntyjärvi J, Kallio S, Savino G, Jozzo L, Marca D (2006) Accelerometer-based gesture control for a design environment. Pers Ubiquit Comput 10:285–299

    Article  Google Scholar 

  9. Keogh E, Pazzani M (2001) Derivative dynamic time warping. Proc. of the First Intl. SIAM Intl. Conf. on Data Mining, Chicago, Illinois

  10. Liu J, Wang Z, Zhong L, Wickramasuriya J, Vasudevan V (2009) “uWave: Accelerometer-based Personalized Gesture Recognition and Its Applications”. Proc. IEEE Int. Conf. Pervasive Computing and Communication (PerCom)

  11. Liu J, Zhong L, Wickramasuriya J, Vasudevan V (2009) User evaluation of lightweight user authentication with a single tri-axis accelerometer. Proc. ACM Int. Conf. Human Computer Interaction with Mobile Devices and Services (MobileHCI), September

  12. Lugmayr A, Dorsch T, Humanes PR, Vallverdu J, ... (eds) (2009) Handbook of research on synthetic emotions and sociable robotics: new applications in affective computing and artificial intelligence, p 443-459. Information Science Reference, IGI Global, Hershey, New York

  13. Maltoni D, Maio D, Jain A, Prabhakar S (2009) Handbook of fingerprint recognition. Springer professional computing, 2nd edn, XVI, p 496. 205 illus.. with DVD

  14. Matsuo K, Okumura F, Hashimoto M, Sakazawa S, Hatori Y (2007) Arm swing identification method with template update for long term stability. Proc. Int. Biometrics

  15. Montpetit MJ, Mirlacher T, Ketcham M (2010) IPTV: An end to end perspective. Journal Commun 5(5):358–373

    Google Scholar 

  16. Nabti M, Bouridane A (2008) An effective and fast iris recognition system based on a combined multiscale feature extraction technique. Pattern Recognit 41:868–879

    Article  MATH  Google Scholar 

  17. Okumura F, Kubota A, Hatori Y, Matsuo K, Hashimoto M, Koike A (2006) A Study on biometric authentication based on arm sweep action with acceleration sensor. Proc. Int. Symp. Intelligent Signal Processing and Communications

  18. Orozco M, Graydon M, Shirmohammadi S, El Saddik A (2008) Experiments in haptic-based authentication of humans. Multimed Tools Appl 37:73–92

    Article  Google Scholar 

  19. Schlömer T, Poppinga B, Henze N, Boll S (2008) Gesture recognition with a Wii Controller. Proceedings of TEI, 11–14

  20. Sedlar U, Zebec L, Bester J, Kos A (2008) Bringing click-to-dial functionality to IPTV users. IEEE Commun Mag 46:118–125

    Article  Google Scholar 

  21. Toledano DT, Pozo RF, Trapote AH, Gómez LH (2006) Usability evaluation of multi-modal biometric verification systems. Interacti Comput 18:1101–1122

    Article  Google Scholar 

  22. Varchol P, Levický D (2007) Using of hand geometry in biometric security systems. Radioengineering:16 (4):82–87

    Google Scholar 

  23. Varona J, Capó AJ, Gonzàlez J, Perales FJ (2009) Toward natural interaction through visual recognition of body gestures in real-time. Interact Comput 21:3–10

    Article  Google Scholar 

  24. Volk M, Sterle J, Sedlar U, Kos A (2010) An approach to modeling and control of QoE in next generation networks. IEEE Commun Mag 48:126–135

    Article  Google Scholar 

  25. Zaharis A, Martini A, Kikiras P, Stamoulis G (2010) User authentication method in implementation using a three-axis acceleoremeter. Mobile Lightweight Wireless Systems, Second International ICST Conference, MOBILIGHT, Springer

  26. Zappi P, Milosevic B, Farella E, Benini L (2009) Hidden Markov Model based gesture recognition on low-cost, low-power tangible user interfaces. Entertain Comput 1:75–84

    Article  Google Scholar 

Download references

Acknowledgments

The operation that led to this paper is partially financed by the European Union, European Social Fund and the Slovenian research Agency, grant No. P2-0246. The authors also thank the participants who took part in the evaluation study.

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000, Ljubljana, Slovenia

    Jože Guna, Emilija Stojmenova, Iztok Humar & Matevž Pogačnik

  2. EMMi - Entertainment and Media Management Lab., Department of Business Information Management and Logistics, Tampere University of Technology (TUT), Korkeakoulunkatu 8, 33101, Tampere, Finland

    Artur Lugmayr

Authors
  1. Jože Guna
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Emilija Stojmenova
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Artur Lugmayr
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Iztok Humar
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Matevž Pogačnik
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Jože Guna.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Guna, J., Stojmenova, E., Lugmayr, A. et al. User identification approach based on simple gestures. Multimed Tools Appl 71, 179–194 (2014). https://doi.org/10.1007/s11042-013-1635-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-013-1635-1

Keywords