A Taxonomy and Dataset for 360° Videos
This work provides a structured dataset and taxonomy for 360° video research, addressing a need in multimedia and VR domains, but it is incremental as it builds on existing categorization efforts without introducing new methods.
The paper tackled the problem of categorizing 360° videos by proposing a taxonomy based on moving objects and camera motion, and created a dataset of 28 videos with viewport traces from 60 participants, including viewer feedback and analysis of viewport patterns.
In this paper, we propose a taxonomy for 360° 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.