The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Dataset for Exploring User Behaviors in VR Spherical Video Streaming
Abstract
With Virtual Reality (VR) devices and content getting increasingly popular, understanding user behaviors in virtual environment is important for not only VR product design but also user experience improvement. In VR applications, the head movement is one of the most important user behaviors, which can reflect a user's visual attention, preference, and even unique motion pattern. However, to the best of our knowledge, no dataset containing this information is publicly available. In this paper, we present a head tracking dataset composed of 48 users (24 males and 24 females) watching 18 sphere videos from 5 categories. We carefully record how users watch the videos, how their heads move in each session, what directions they focus, and what content they can remember after each session. Based on this dataset, we show that people share certain common patterns in VR spherical video streaming, which are different from conventional video streaming. We believe the dataset can serve good resource for exploring user behavior patterns in VR applications.
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Cites
Viewport-adaptive navigable 360-degree video delivery
Corbillon, X., Simon, G., Devlic, A., & Chakareski, J. (2017) · 2017 IEEE International Conference on Communications (ICC) · doi:10.1109/icc.2017.7996611 · Cited by 341
Cited by
State-of-the-Art in 360° Video/Image Processing: Perception, Assessment and Compression
Xu, M., Li, C., Zhang, S., & Callet, P. L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.2966864 · Cited by 281
NetLLM: adapting large language models for networking
Wu, D., Wang, X., Qiao, Y., Wang, Z., Jiang, J., Cui, S., & Wang, F. (2024) · Proceedings of the ACM SIGCOMM 2024 Conference · doi:10.1145/3651890.3672268 · Cited by 167
Self-citationSplit Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions
Hafi, H., Brik, B., Frangoudis, P. A., Ksentini, A., & Bagaa, M. (2024) · IEEE Access · doi:10.1109/access.2024.3351600 · Cited by 90
LiveDeep: Online Viewport Prediction for Live Virtual Reality Streaming Using Lifelong Deep Learning
Feng, X., Liu, Y., & Wei, S. (2020) · 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr46266.2020.00104 · Cited by 45
LiveObj: Object Semantics-based Viewport Prediction for Live Mobile Virtual Reality Streaming
Feng, X., Bao, Z., & Wei, S. (2021) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2021.3067686 · Cited by 34
Metadata
- Authors
- Wu, C., Tan, Z., Wang, Z., & Yang, S.
- Venue
- Proceedings of the 8th ACM on Multimedia Systems Conference
- Publisher
- ACM
- Published
- 2017-06-20
- Pages
- 193-198
- OpenAlex
- W2622637199
- Cited by
- 260
- References
- 1
- FWCI
- 19.81
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wu, C., Tan, Z., Wang, Z., & Yang, S. (2017). A Dataset for Exploring User Behaviors in VR Spherical Video Streaming. Proceedings of the 8th ACM on Multimedia Systems Conference. https://doi.org/10.1145/3083187.3083210
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