Skip to main content
SpringerLink
Log in
Book cover

International Conference on Artificial Intelligence and Soft Computing

ICAISC 2021: Artificial Intelligence and Soft Computing pp 463–474Cite as

Intelligent Virtual Environments with Assessment of User Experiences

  • Conference paper
  • First Online:

  • 1042 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

Abstract

Virtual reality (VR) is a powerful modern medium. The advent of low-cost head-mounted display (HMD) devices made this technology accessible at large and featured VR with possibilities to monitor interactions and user’s motion. However, due to lack of real-time feedback mechanism at present, the level of intelligence for virtual environments is still not sufficient to assist the experience and make group or individual assessments towards VR based applications. In this paper, we present our findings related to the problem of real-time feedback that focus on behavioral data by employing the novel feedback mechanism. Virtual-world coordinates, motions and interactions are tracked and captured in real-time while the user experiences particular application. Captured data is investigated to target the issue of complementing VR applications with features derived from real-time behavioral analysis. In our experiment, we also use collected data and provide a methodology to predict virtual-location by the nonlinear auto-regressive neural network with exogenous inputs (NARX). Results suggest employed neural network model is suitable for performing prediction which can be used to obtain a virtual environment with adaptive intelligence.

Supported by the Estonian Research Council grant PRG658.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Sherman, W., Craig, A.: Understanding Virtual Reality. Elsevier (2019)

    Google Scholar 

  2. Kivikangas, J.M., et al.: A review of the use of psychophysiological methods in game research. J. Gaming Virtual Worlds 3(3), 181–199 (2011)

    Article  Google Scholar 

  3. Soler-Domínguez, J.L., Contero, M., Alcañiz, M.: Workflow and tools to track and visualize behavioural data from a virtual reality environment using a lightweight GIS. SoftwareX 10, 100269 (2019)

    Article  Google Scholar 

  4. Pan, X., de C Hamilton, A.F.: Why and how to use virtual reality to study human social interaction: the challenges of exploring a new research landscape. Br. J. Psychol. 109(3), 395–417 (2018)

    Google Scholar 

  5. Turk, M.: Multimodal interaction: a review. Pattern Recogn. Lett. 36, 189–195 (2014)

    Article  Google Scholar 

  6. Hansberger, J.T., Peng, C., Blakely, V., Meacham, S., Cao, L., Diliberti, N.: A multimodal interface for virtual information environments. In: Chen, J.Y.C., Fragomeni, G. (eds.) HCII 2019. LNCS, vol. 11574, pp. 59–70. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21607-8_5

    Chapter  Google Scholar 

  7. Hunt, H.T.: Why psychology is/is not traditional science: the self-referential bases of psychological research and theory. Rev. Gen. Psychol. 9(4), 358–374 (2005)

    Article  Google Scholar 

  8. Lanier, M., et al.: Virtual reality check: statistical power, reported results, and the validity of research on the psychology of virtual reality and immersive environments. Comput. Hum. Behav. 100, 70–78 (2019)

    Article  Google Scholar 

  9. Zhang, S., Yao, L., Sun, A., Tay, Y.: Deep learning based recommender system. ACM Comput. Surv. 52(1), 1–38 (2019)

    Google Scholar 

  10. Eaves, D.L., Breslin, G., van Schaik, P.: The short-term effects of real-time virtual reality feedback on motor learning in dance. Presence Teleoperators Virtual Environ. 20(1), 62–77 (2011)

    Article  Google Scholar 

  11. Johnson, A., Tang, Y., Franzwa, C.: kNN-based adaptive virtual reality game system. In: Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control. IEEE (April 2014)

    Google Scholar 

  12. Jayaraj, L., Wood, J., Gibson, M.: Improving the immersion in virtual reality with real-time avatar and haptic feedback in a cricket simulation. In: 2017 IEEE International Symposium on Mixed and Augmented Reality. IEEE (October 2017)

    Google Scholar 

  13. Reski, N., Alissandrakis, A.: Open data exploration in virtual reality: a comparative study of input technology. Virtual Reality 24(1), 1–22 (2019)

    Article  Google Scholar 

  14. Serpanos, D., Wolf, T.: Architecture of Network Systems. Elsevier (2011)

    Google Scholar 

  15. Epic Games: Unreal Engine. https://www.unrealengine.com/en-US. Accessed 03 Jun 2020

  16. Smyth, D.L., Glavin, F.G., Madden, M.G.: Using a game engine to simulate critical incidents and data collection by autonomous drones. In: 2018 IEEE Games, Entertainment, Media Conference (GEM). IEEE (August 2018)

    Google Scholar 

  17. Merino, L., Ghafari, M., Anslow, C., Nierstrasz, O.: CityVR: gameful software visualization. In: 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE (September 2017)

    Google Scholar 

  18. Paliokas, I., Kekkeris, G., Georgiadou, K.: Study of users’ behaviour in virtual reality environments. Int. J. Technol. Knowl. Soc. 4(1), 121–132 (2008)

    Article  Google Scholar 

  19. Grivokostopoulou, F., Perikos, I., Hatzilygeroudis, I.: An innovative educational environment based on virtual reality and gamification for learning search algorithms. In: 2016 IEEE 8th International Conference on Technology for Education (T4E). IEEE (December 2016)

    Google Scholar 

  20. Kose, A., Tepljakov, A., Abel, M., Petlenkov, E.: Towards assessment of behavioral patterns in a virtual reality environment. In: De Paolis, L.T., Bourdot, P. (eds.) AVR 2019. LNCS, vol. 11613, pp. 237–253. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-25965-5_18

    Chapter  Google Scholar 

  21. Pfeuffer, K., Geiger, M.J., Prange, S., Mecke, L., Buschek, D., Alt, F.: Behavioural biometrics in VR. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019. ACM Press (2019)

    Google Scholar 

  22. Millais, P., Jones, S.L., Kelly, R.: Exploring data in virtual reality. In: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems - CHI. ACM Press (2018)

    Google Scholar 

  23. Moran, A., Gadepally, V., Hubbell, M., Kepner, J.: Improving big data visual analytics with interactive virtual reality. In: 2015 IEEE High Performance Extreme Computing Conference (HPEC). IEEE (September 2015)

    Google Scholar 

  24. LaValle, S.M.: Planning Algorithms. Cambridge University Press (2006)

    Google Scholar 

  25. Moré, J.J.: The Levenberg-Marquardt algorithm: implementation and theory. In: Watson, G.A. (ed.) Numerical Analysis. LNM, vol. 630, pp. 105–116. Springer, Heidelberg (1978). https://doi.org/10.1007/BFb0067700

    Chapter  Google Scholar 

  26. Ibrahim, M., Jemei, S., Wimmer, G., Hissel, D.: Nonlinear autoregressive neural network in an energy management strategy for battery/ultra-capacitor hybrid electrical vehicles. Electr. Power Syst. Res. 136, 262–269 (2016)

    Article  Google Scholar 

  27. Maranes, C., Gutierrez, D., Serrano, A.: Exploring the impact of \(360^{\circ }\) movie cuts in users’ attention. In: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). IEEE (March 2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Akadeemia tee 15a, 12618, Tallinn, Estonia

    Ahmet Köse, Aleksei Tepljakov & Eduard Petlenkov

Authors
  1. Ahmet Köse
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aleksei Tepljakov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eduard Petlenkov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmet Köse .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Köse, A., Tepljakov, A., Petlenkov, E. (2021). Intelligent Virtual Environments with Assessment of User Experiences. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-87986-0_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation