Emotional Attention: From Eye Tracking to Computational Modeling.

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 attention. We create the EMOtional attention dataset (EMOd).

Image Visual Realism: From Human Perception to Machine Computation.

Visual realism is defined as the extent to which an image appears to people as a photo rather than computer generated. Assessing visual realism is important in applications like computer graphics rendering and photo retouching. However, current realism evaluation approaches use either labor-intensive human judgments or automated algorithms largely dependent on comparing renderings to reference images.

Revealing the world of autism through the lens of a camera.

People with autism spectrum disorder (ASD) show atypical attention to social stimuli [1] and gaze at faces [2] and complex images [3] in unusual ways. But all studies to date are limited by the experimenter's selected stimuli, which are generally photographs taken by people without autism. What might participants with ASD show us if they were the ones taking the photos? We gave participants a digital camera and analysed the photos they took: images taken by participants with ASD had unusual features and showed strikingly different ways of photographing other people.