VR Flow - Likes and Dislikes

Closed Human-Computer Interaction Computer Science Games Engineering Bachelor Master Project Thesis Games Research Lab

Background

This project aims at interpreting the user/player behaviour of immersive experiences and games. It utilises heuristics to interpret the user’s interactions with and reactions to specific contents in order to infer how attractive/unattractive the contents are. As a next step, these heuristics could be used to generate and adapt tailor-fit virtual contents for game levels or serious game contents on-the-fly. To begin with, VR Flow aims at basic research at the border between embodiment and behavioural psychology. One needs to design strategically sound experiments in order to capture and quantitatively measure the impact of interactive, dynamic contents on the user’s behaviour. The complexity of visual stimuli can, for instance, be scaled through combinations of pre-attentive attributes such as movement, colour and shape of visual elements. According particle systems can be easily setup in immersive environments. Next, the user’s behaviour needs to be traced. The HMD’s position and orientation in relation to the contents provide immediate feedback about the user’s focus. This will allow to infer the user’s eagerness/reluctance to consume the offered contents.

Tasks

In a room-scale VR setup, the effective perception space should be measured individually. After this calibration phase, visual information is presented that the user can either consume (by looking at it) or ignore (by looking away). Tasking the user with identifying certain objects in a stream of visual stimuli will ensure that there is incentive in consuming the contents. The complexity of the visual stimuli should be scaled across the perception space. Higher complexity would also provide slightly higher incentives/scores, whereas lower visual complexity might be more accessible/acceptable for the user to consume. As a result, the user will adapt his focus to the flow of information he perceives as the best trade-off between gains and efforts. The full parameterisation of the content creation model in combination with the continuous recognition of the user’s behaviour will allow us to adapt the contents to establish an optimal, individual flow and, for the user, to maximally prolong the immersive experience and to maximise the score. A comprehensive user study needs to support an identified model for visual complexity flow in VR.

Prerequisites

A background in HCI, VR and 3D engines is a great asset for this work.

References

[1] M Csikszentmihaiyi. Flow: The Psychology of Optimal Experience. New York: Harper and Row, 1990.

[2] Raph Koster. Theory of fun for game design. O’Reilly Media, Inc., 2013.

[3] Penelope Sweetser and Peta Wyeth. Gameflow: a model for evaluating player enjoyment in games. Computers in Entertainment (CIE), 3(3):3–3, 2005.

Contact Persons at the University Würzburg