User Attention and Behaviour in Virtual Reality Art Encounter

TL;DR

This paper investigates user attention and behavior in virtual reality art encounters by developing an experimental system, analyzing user data with deep learning, and creating visualization methods to inform VR content creation.

Contribution

It introduces a novel VR art exploration system, analyzes user behavior patterns, and develops integrated visualization techniques for audience attention in VR environments.

Findings

Identified diverse user activity patterns in VR art exploration.

Deep learning models reveal connections between user behavior and background.

Developed visualization methods for real-time user attention feedback.

Abstract

With the proliferation of consumer virtual reality (VR) headsets and creative tools, content creators have started to experiment with new forms of interactive audience experience using immersive media. Understanding user attention and behaviours in virtual environment can greatly inform creative processes in VR. We developed an abstract VR painting and an experimentation system to study audience encounters through eye gaze and movement tracking. The data from a user experiment with 35 participants reveal a range of user activity patterns in art exploration. Deep learning models are used to study the connections between behavioural data and audience background. New integrated methods to visualise user attention as part of the artwork are also developed as a feedback loop to the content creator.