Prediction of Pending Data Using Interpolation and Extrapolation Techniques for Virtual Rowing

Authors

Keywords:

virtual reality, data prediction, peripheral device, interpolation, extrapolation, latency

Abstract

The use of peripheral devices could be a good alternative to interact with Virtual Environment in addition to native controllers. Using combination of Concept-II peripheral device with VR mobile will cause latency issues due to different data transmission rates between those components. This latency issue leads to two major problems, such as micro-stutter in Virtual Environment (VE) and distance inaccuracy in time between the Concept-II peripheral device and VR mobile. In this paper, the authors present three algorithms based on interpolation and extrapolation methods, which aim to provide immersive VR experience by ensuring stutter-free and accurate rowing sessions for the user. This is relevance when considering the adoption of peripheral devices (i.e. the Concept-II peripheral device) as an alternative to interact with Virtual Environment in addition to native controllers. Predicting virtual rowing shell’s position using interpolation by position method gives accurate time results but introduces high amount of micro-stutter. Using extrapolation method by taking speed parameter to predict rowing shell’s position has very high time error but gives pleasant, stutter-free virtual rowing experience. Finally, adding this speed parameter a correction constant value for predicting virtual rowing shell’s position provides stutter-free and very accurate in time rowing session for the user.

Author Biography

Cenker Canbulut, Kaunas University of Technology

Cenker Canbulut is a third-year PhD student and full time lecturer at Kaunas University of Technology in Software Engineering Department. He received his bachelor and master's degree in same university at the same department. His current field is "Virtual Reality control methods using natural user interface components". He is interested on improving Virtual Reality control methods to provide additional methods to control Virtual Environment and its elements.

References

Black, R.; Landauer, J.; Rösch, A.; Simon, A. (1998). A highly flexible virtual reality system, Future Generation Computer Systems, 14(3-4), 167-178, 1998. https://doi.org/10.1016/S0167-739X(98)00019-3

Ceccotti, H.; Volosyak, I.; Gräser, I. (2010). Reliable visual stimuli on LCD screens for SSVEP based BCI, 18th European Signal Processing Conference, IEEE, 919-923,2010.

Desai, P.R.; Desai, P.N.; Ajmera, K.D., and Mehta, K. (2014). A Review Paper on Oculus Rift, International Journal of Engineering Trends and Technology (IJETT), 13(4), 175-179, 2014. https://doi.org/10.14445/22315381/IJETT-V13P237

Emura, S.; Tachi, S. (1998). Multisensor Integrated Prediction for Virtual Reality, Presence: Teleoperators and Virtual Environments, 7(4), 410-422, 1988. https://doi.org/10.1162/105474698565811

Friedmann, M.; Starner, T.; Pentland, A. (1992). Synchronization in Virtual Realities, Presence: Teleoperators and Virtual Environments, 1(1), 139-144, 1992. https://doi.org/10.1162/pres.1992.1.1.139

Gutierrez, M.; Vexo, F.; Thalmann, D. (2008). Stepping into virtual reality, Springer, 2008. https://doi.org/10.1007/978-1-84800-117-6

Gutmann, G.; Konagaya, A. (2019). Predictive Simulation: Using Regression and Artificial Neural Networks to Negate Latency in Networked Interactive Virtual Reality Computer Science ArXiv 2019, Tokyo, 2019.

He, S.; Liu, Y.; Zhou, H. (2015). Optimizing Smartphone Power Consumption through Dynamic Resolution Scaling, Proceedings of the 21st Annual International Conference on Mobile Computing and Networking - MobiCom '15, 27-39, 2015. https://doi.org/10.1145/2789168.2790117

Hou, X.; Sourina, O. (2013). A prediction method using interpolation for smooth six-DOF haptic rendering in multirate simulation, 2013 International Conference on Cyberworlds, CW 2013, IEEE, 294-301, 2013. https://doi.org/10.1109/CW.2013.43

Iskandar, Y.H.; Gilbert, L.; Wills, G.B. (2008). Reducing latency when using Virtual Reality for teaching in sport, 2008 International Symposium on Information Technology, IEEE, 3, 1-5, 2008. https://doi.org/10.1109/ITSIM.2008.4632076

Jung, J.Y; Adelstein, B.D; Ellis, S.R (2000). Discriminability of Prediction Artifacts in a Time- Delayed Virtual Environment, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 44(5), 499-502, 2000. https://doi.org/10.1177/154193120004400504

Lambeta, M.; Dridger, M.; White, P.; Janssen J.; and Byagowi, A. (2016). Haptic wheelchair, SIGGRAPH 2016 - AC SIGGRAPH 2016 Posters. https://doi.org/10.1145/2945078.2945168

Lee, J.; Kim, M.; Kim, J. (2017). A Study on Immersion and VR Sickness in Walking Interaction for Immersive Virtual Reality Applications, Symmetry, 9(5), 78, 2017. https://doi.org/10.3390/sym9050078

Matica, L. M.; Oros, H. (2017). Speed Computation for Industrial Robot Motion by Accurate Positioning, International Journal of Computers Communications & Control, 12(1), 76-89, 2017. https://doi.org/10.15837/ijccc.2017.1.2785

Michaeli, T.; Pohl, V.; Member, S.; Eldar, Y.C. (2011). U-Invariant Sampling : Extrapolation and Causal Interpolation From Generalized Samples, IEEE Transactions on Signal Processing, 59(5), 2085-2100, 2011. https://doi.org/10.1109/TSP.2011.2113342

Pan, M.K.X.J.; Niemeyer, G. (2017). Catching a real ball in virtual reality, IEEE Virtual Reality (VR), 4, 269-270, 2017. https://doi.org/10.1109/VR.2017.7892280

Papson, S.; Oagaro, J.; Polikar, R.; Chen, J.C; Schmalzel, J.L; Mandayam, S. (2004). A Virtual Reality Environment for Multi-Sensor Data Integration, Proceedings of the ISA/IEEE Sensors for Industry Conference, IEEE, 116-122, 2004.

Russel, M.T.(2018). Virtual Reality System Concepts Illustrated Using OSVR Published in the book VR Gems in 2018, CRC Press, 2018.

Sturges, H.A. (1926). The Choice of a Class Interval, Journal of the American statistical association, 21(153), 65-66, 1926. https://doi.org/10.1080/01621459.1926.10502161

Velden, D.V. (2017). Touchpad in VR: Evaluating input devices in virtual reality, Master's thesis, Utrecht, 2017.

Von Zitzewitz, J.; Wolf, P.; Novakovic, V. (2009). Real-time rowing simulator with multi-modal feedback, Sports Technology, 1(6), 257-266, 2009. https://doi.org/10.1080/19346182.2008.9648483

Zhao, D.; Yang, T.; Ou, W.; Zhou, H. (2018). Autopilot Design for Unmanned Surface Vehicle based on CNN and ACO, International Journal of Computers Communications & Control, 15(1), 429-439, 2018. https://doi.org/10.15837/ijccc.2018.3.3236

Published

2020-03-28

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