We present an approach to bridge the gap between the computational models of human
vision and the clinical practice on visual impairments (VI). In a nutshell, we propose to …

Convolutional neural networks (CNNs) have significantly advanced computational
modelling for saliency prediction. However, accurately simulating the mechanisms of visual …

Since 2014 transfer learning has become the key driver for the improvement of spatial
saliency prediction-however, with stagnant progress in the last 3-5 years. We conduct a …

Visual ambiguity plays a key role in the perceptual experience of art and has been much
exploited by modernist and contemporary artists for aesthetic effects. But it remains unclear …

To further advance driver monitoring and assistance systems, it is important to understand
how drivers allocate their attention, in other words, where do they tend to look and why …

Attending selectively to emotion-eliciting stimuli is intrinsic to human vision. In this research,
we investigate how emotion-elicitation features of images relate to human selective …

Previous studies have shown that there is a strong correlation between radiologists'
diagnoses and their gaze when reading medical images. The extent to which gaze is …

We propose a computational model to estimate a person's attended awareness of their
environment. We define" attended awareness" to be those parts of a potentially dynamic …

Saliency models seek to predict fixation locations in (human) gaze behaviour. These are
typically created to generalize across a wide range of visual scenes but validated using only …

Visual working memory (VWM) is a cognitive mechanism essential for interacting with the
environment and accomplishing ongoing tasks, as it allows fast processing of visual inputs …