Spherical Clustering of Users Navigating 360 Content

In Virtual Reality (VR) applications, understanding how users explore the omnidirectional content is important to optimize content creation, to develop user-centric services, or even to detect disorders in medical applications. Clustering users based on their common navigation patterns is a first direction to understand users behavior. However, classical clustering techniques fail in identifying this common paths, since they are usually focused on minimizing a simple distance metric. In this paper, we argue that minimizing the distance metric does not necessarily guarantee to identify users that experience similar navigation path in the VR domain. Therefore, we propose a graph-based method to identify clusters of users who are attending the same portion of the spherical content over time. The proposed solution takes into account the spherical geometry of the content and aims at clustering users based on the actual overlap of displayed content among users. Our method is tested on real VR user navigation patterns. Results show that our solution leads to clusters in which at least 85% of the content displayed by one user is shared among the other users belonging to the same cluster.


Published in:
2019 IEEE InternationalConference on Acoustics, Speech,and Signal Processing. Proceedings,
Presented at:
ICASSP 2019 - IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 12-17 May, 2019
Year:
2019
Publisher:
IEEE
ISBN:
978-1-4799-8131-1
Additional link:
Laboratories:




 Record created 2019-08-08, last modified 2019-08-12


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