ATTENTION: This is a web archive! The IMS Group was split up in 2018 and does not exist anymore. Recent work of former members can be found at the VR/AR Group and the Computer Vision Group.

Interactive Media Systems, TU Wien

Preventing Imminent Collisions between Co-Located Users in HMD-Based VR in Non-Shared Scenarios

By Iana Podkosova and Hannes Kaufmann


This paper presents two experiments set in a multi-user HMD-based VR system where users navigate by real walking in a large real and vir- tual area. We investigate a case that could be used in a multi-user VR game or a training ap- plication: several users are walking in the same physical space without seeing each other in the virtual environment. Such a scenario involves the risk of collisions between users. In the first experiment, we investigate the strategy of stop- ping a walking user in a dangerous situation. In particular, we compare the effectiveness and the perceived difficulty of two visual and two audi- tory stopping signals. The results of this com- parison show that the tested visual and auditory signals are equally effective in stopping users. With both visual and auditory signals, partici- pants prefer the signal to contain a "stop" com- mand. In the second experiment, avatars are displayed at users´ positions if the distance be- tween users is dangerously small. The method is tested with four avatars of various degrees of anthropomorphism and in two different appli- cation scenarios. Our results suggest that the type of scenario influences users´ preference of a notification avatar. It is sufficient to display an area occupied by other users in scenarios with specific goals and interactive content. If users are exploring a virtual world without hav- ing any other goal, they prefer to see human- like avatars as a possible collision notification.


I. Podkosova, H. Kaufmann: "Preventing Imminent Collisions between Co-Located Users in HMD-Based VR in Non-Shared Scenarios"; Talk: CASA 2017, Seoul, South Korea; 05-22-2017 - 05-24-2017; in: "Proceedings of the 30 th International Conference on Computer Animation and Social Agents", CASA 2017, (2017), ISBN: 978-89-89453-82-6; 37 - 46.


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