The research domain on the Quality of Experience (QoE) of 2D video streaming has been well established. However, a new video format is emerging and gaining popularity and availability: VR 360-degree video. The processing and transmission of 360-degree videos brings along new challenges such as large bandwidth requirements and the occurrence of different distortions. The viewing experience is also substantially different from 2D video, it offers more interactive freedom on the viewing angle but can also be more demanding and cause cybersickness. Further research on the QoE of 360-videos specifically is thus required.The first goal of this thesis is to complement earlier research by (Tran, Ngoc, Pham, Jung, and Thank, 2017) testing the effects of quality degradation, freezing, and content on the QoE of 360-videos. The second goal is to test the contribution of visual attention as influence factor in the QoE assessment. Data will be gathered through subjective tests where participants watch degraded versions of 360-videos through an HMD with integrated eye-tracking sensors. After each video they will answer questions regarding their quality perception, experience, perceptual load, and cybersickness.Results of the first part show overall rather low QoE ratings and it decreases even more as quality is degraded and freezing events are added. Cyber sickness was found not to be an issue. The effects of the manipulation on visual attention were minimal. Attention was mainly directed by content, but also by surprising elements. The addition of eye-tracking metrics did not further explain individual differences in subjective ratings. Nevertheless it was found that looking at moving objects increased the negative effect of freezing events and made participants less sensitive for quality distortions. The results of this thesis alone are not enough to successfully regard visual attention as an influence factor in 360-video.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ri-39963 |
| Date | January 2019 |
| Creators | van Kasteren, Anouk |
| Publisher | RISE - Research Institutes of Sweden (2017-2019), Acreo, University of Technology Eindhoven, Netherlands |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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