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Interactive, multi-user experiences are meant to define the present and future of Virtual Reality (VR). Such immersive experiences will typically consist of remote collaborations where content is streamed and/or synchronized over a network connection. Thus, real-time collaboration will be key. In this light, the responsiveness of the system and the network will define the overall experience. As such, understanding the effect of network distortions, especially related to time delay, on end-user’s perception (in terms of Quality-of-Experience (QoE)), performance, and collaboration becomes crucial. The existing literature, however, has mostly focused on network requirements from a system point-of-view, where the key performance parameters are only provided in the form of Quality-of-Service (QoS) parameters (such as end-to-end latency). However, the translation of these network impairments to the end-user experience is often omitted. The purpose of this paper is to fill the gap by providing a thorough investigation of the impact of latency on the perception of users while performing collaborative tasks in multi-user VR. To this end, an experimental framework was designed, developed, and tested. It is based on a multi-device synchronizing architecture, enabling two simultaneous users to work together in a gamified virtual environment. The developed test environment also allows for the identification of the most prominent network requirements and objective analysis for each traffic link. To experimentally investigate the impact of latency on user perception, a user study was conducted. Participants were paired and asked to perform the collaborative task under different latency-prone scenarios. The results show that users are able to easily distinguish between distorted and non-distorted network configurations. However, making a distinction between different manifestations of latency is much less straightforward. Moreover, factors such as the user’s role in the experience and the required task, and the level of interactivity and movement have an important influence on the subjective level of perception, the strength of the user’s preferences, and the occurrence of cybersickness. In contrast, no significant differences in objective metrics, such as system performance and user completion time were observed. These results can support the creation of collective QoE metrics that model the group as a whole rather than each individual separately. As such, this work provides an important step to dynamically counteract any drops in group dynamics and performance by means of smart interventions in the transmission system and/or virtual environment. |
