Creating a Personalised Museum Experience with Deep Learning

Individual preferences for Art, like beauty, are thought to be in the eye of the beholder. But can science find away to identify what we really appreciate in paintings? Delving into the mindset of a person’s visual preferences has proven challenging, as an objective method to separate their liking of a painting’s content from its artistic style does not exist yet. For example, does someone find paintings of Van Gogh pleasing because of the application of brushstrokes or the choice of content, such as sunflowers? We suggest a novel approach to tackle this question, bringing together the latest advances in engineering, computational modelling and virtual reality and combining them with experimental psychology and art. Using eye-tracking and deep learning, it is now possible to develop tools capable of providing real-time feedback about a person’s visual (aesthetic) preferences. This is a crucial step towards strategically curated exhibitions tailored to an individual’s preferences and sensibilities. This project promises to create striking new experiences that captivate the public and reshape museums for the audiences of the future.