The advent in our daily life of Extended Reality (XR) technologies, such as Virtual and Augmented Reality, has led to the rise of user-centric systems, offering higher level of interaction and presence in virtual environments. In this context, understanding the actual interactivity of users is still an open challenge and a key step to enabling user-centric system. In this work, our goal is to construct an efficient clustering tool for 6 df navigation trajectories by extending the applicability of existing behavioural tool. Specifically, we first compare the navigation in 6 df with its 3 df counterpart, highlighting the main differences and novelties. Then, we investigate new metrics aimed at better modelling behavioural similarities between users in a 6 df system. More concretely, we define and compare 11 similarity metrics which are based on different distance features (i.e., user positions in the 3D space, user viewing directions) and distance measurements (i.e., Euclidean, Geodesic, angular distance). Our solutions are validated and tested on real navigation paths of users interacting with dynamic volumetric media in both 6 df Virtual Reality and Augmented Reality conditions. Results show that metrics based on both user position and viewing direction better perform in detecting user similarity while navigating in a 6 df system. Such easy-to-use but robust metrics allow us to answer a fundamental question for user-centric systems: ‘How do we detect if users look at the same content in 6 df?’, opening the gate to new solutions based on users interactivity, such as viewport prediction, live streaming services optimised based on users behaviour but also for user-based quality assessment methods.

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.

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.

Thanks to recent advances in computer graphics, wearable technology, and connectivity, Virtual Reality (VR) has landed in our daily life. A key novelty in VR is the role of the user, which has turned from merely passive to entirely active. Thus, improving any aspect of the coding–delivery–rendering chain starts with the need for understanding user behaviour. To do so, we investigate the navigation trajectories of users within a 6-Degrees-of-Freedom (DoF) VR environment. Specifically, we investigate the main differences and similarities between 3 and 6-DoF navigation through existing methodologies adopted to study user behaviour in 3-DoF settings. Our simulation results, based on real navigation paths of users while displaying dynamic volumetric media in 6-DoF conditions, show the limitations of clustering algorithms for 3-DoF in assessing user similarity in 6-DoF. Given these observations, we state the need for developing new solutions for the analysis of 6-DoF trajectories.