Research on visual attention in 360 • content is crucial to understand how people perceive and interact with this immersive type of content and to develop efficient techniques for processing, encoding, delivering and rendering. And also to offer a high quality of experience to end users. The availability of public datasets is essential to support and facilitate research activities of the community. Recently, some studies have been presented analyzing exploration behaviors of people watching 360 • videos, and a few datasets have been published. However, the majority of these works only consider head movements as proxy for gaze data, despite the importance of eye movements in the exploration of omnidirectional content. Thus, this paper presents a novel dataset of 360 • videos with associated eye and head movement data, which is a follow-up to our previous dataset for still images [14] . Head and eye tracking data was obtained from 57 participants during a free-viewing experiment with 19 videos. In addition, guidelines on how to obtain saliency maps and scanpaths from raw data are provided. Also, some statistics related to exploration behaviors are presented, such as the impact of the longitudinal starting position when watching omnidirectional videos was investigated in this test. This dataset and its associated code are made publicly available to support research on visual attention for 360 • content.
David et al. provided a dataset of head and eye movements REF for nineteen videos watched by 57 subjects.
A dataset of head and eye movements for 360° videos
MMSys '18
Computer Science