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 dis- tance metric does not necessarily guarantee to identify users that ex- perience 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.

IEEE International Conference on Acoustics, Speech, and Signal Processing
Distributed and Interactive Systems

Rossi, S, De Simone, F, Frossard, P, & Toni, L. (2019). Spherical clustering of users navigating 360-degree content. In Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019).