# A Taxonomy and Dataset for 360deg Videos

arXiv: https://arxiv.org/abs/1905.03823 · HTML: https://mlsanity.com/paper/1905.03823/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 May 2019.

## Built on by (most cited first, 4 of 4)

- [A review on Machine Learning based User-Centric Multimedia Streaming Techniques](https://mlsanity.com/paper/2411.15801/) (2024)
- [A Systematic Investigation on Deep Learning-Based Omnidirectional Image and Video Super-Resolution](https://mlsanity.com/paper/2506.06710/) (2025)
- [Omnidirectional Video Super-Resolution using Deep Learning](https://mlsanity.com/paper/2506.14803/) (2025)
- [Generating Realistic Synthetic Head Rotation Data for Extended Reality using Deep Learning](https://mlsanity.com/paper/2501.09050/) (2025)

## Abstract (arXiv)

In this paper, we propose a taxonomy for 360deg videos that categorizes videos based on moving objects and camera motion. We gathered and produced 28 videos based on the taxonomy, and recorded viewport traces from 60 participants watching the videos. In addition to the viewport traces, we provide the viewers' feedback on their experience watching the videos, and we also analyze viewport patterns on each category.