This work presents an explorative behavioural analysis of users navigating in an immersive space aimed at enabling the next-generation multimedia systems. Our main goal is to understand how the user experience of immersive content with 6-Degrees-of-Freedom (DoF) is affected not only by the visual content and its quality but also by the disposition of the user. We based our investigations on traditional statistical metrics, on techniques that have been already used for 6-DoF, as well as adapted 3-DoF tools to be used in this new context. We show the limitation of each metric in giving a complete interpretation of user behaviour, and we draw insights on important factors to be considered when analysing and predicting navigation trajectories. Specifically, we have noticed in our behavioural investigations that the user disposition plays an important role in the way of interacting with the immersive content. This opens the gate to user profiles (i.e., a collection of key information that describes the behavioural features of a single or group of users) that would be beneficial for different purposes in future immersive applications such as enabling new modalities for live streaming services optimised per user profiles but also for user-based quality assessment methods. @en

Immersive reality technologies, such as Virtual and Augmented Reality, have ushered a new era of user-centric systems, in which every aspect of the coding-delivery-rendering chain is tailored to the interaction of the users. Understanding the actual interactivity and behaviour of the users is still an open challenge and a key step to enabling such a user-centric system. Our main goal is to extend the applicability of existing behavioural methodologies for studying user navigation in the case of 6 Degree-of-Freedom (DoF). Specifically, we first compare the navigation in 6-DoF with its 3-DoF counterpart highlighting the main differences and novelties. Then, we define new metrics aimed at better modelling behavioural similarities between users in a 6-DoF system. We validate and test our solutions on real navigation paths of users interacting with dynamic volumetric media in 6-DoF Virtual Reality conditions. Our results show that metrics that consider both user position and viewing direction better perform in detecting user similarity while navigating in a 6-DoF system. Having easy-To-use but robust metrics that underpin multiple tools and answer the question "how do we detect if two users look at the same content?"open the gate to new solutions for a user-centric system. @en

Social Virtual Reality (VR) applications represent a big step forward in the field of remote communication. Social VR provides the possibility for participants to explore and interact with virtual environments and objects, feelings of a full sense of immersion, and being together. Understanding how user behaviour is influenced by the shared virtual space and its elements becomes the key to design and optimize novel immersive experiences. This paper presents a behavioural analysis of user navigating in 6 degrees of freedom social VR movie. Specifically, we analyse 48 user trajectories from a photorealistic telepresence experiment, in which subjects watch a crime movie together in VR. We investigate how users are affected by salient agents (i.e., virtual characters) and by narrative elements of the VR movie (i.e., dialogues versus interactive part). We complete our assessment by conducting a statistical analysis of the collected data. Results indicate that user behaviour is affected by different narrative and interactive elements. We conclude by presenting our observations and drawing conclusions on future paths for social VR experiences. This work has been supported by Royal Society under grant IES R1180128 and by Cisco under Cisco Research Center Donation scheme.@en

In recent years, a large variety of online communication tools have emerged, including social Virtual Reality (VR) platforms for interacting in a virtual world with participants being represented as virtual avatars. Given their popularity, an active area of research focuses on improving the user experience in these virtual experiences. To enable experimentation at large scale on online platforms, it is however essential to collect behavioural data (e.g. movements and audio information). In this work, we present a toolchain that enables the running of experiments using a modified version of the social VR platform Mozilla Hubs. Specifically, our toolkit enables collection and tracking or user positions and movements at a central location, enabling fine-grained analysis of user behaviour during a social VR experience.@en