Simulator Sickness Assessment for $$360^\circ $$ Videos
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49988-3_6
Reference11 articles.
1. R.S. Kennedy et al., Simulator sickness questionnaire: an enhanced method for quantifying simulator sickness. Int. J. Aviat. Psychol. 3(3), 203–220 (1993)
2. J. Kim et al., Virtual reality sickness predictor: analysis of visual-vestibular conflict and VR contents, in 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX) (2018), pp. 1–6. https://doi.org/10.1109/QoMEX.2018.8463413
3. H.G. Kim et al., VRSA net: VR sickness assessment considering exceptional motion for 360-degree VR video. IEEE Trans. Image Process. 28(4), 1646–1660 (2019). https://doi.org/10.1109/TIP.2018.2880509
4. ITU-T Rec. P.910, Recommendation ITU-T P.910: subjective video quality assessment methods for multimedia applications (2008)
5. N. Padmanaban et al., Towards a machine-learning approach for sickness prediction in 360-degree stereoscopic videos. IEEE Trans. Vis. Comput. Graph. 24, 1594–1603 (2018)
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