The first principal goal of the project is to develop models of attentional selection in scene viewing that account for the viewer’s familiarity with a visual scene and for conceptually-driven anticipation of the image content as well as for viewer-specific distributional properties of fixational patterns. The second principal goal is to leverage these generative models of fixation sequences into discriminative models that accurately predict values of latent variables, such as levels of familiarity, based on a given fixation sequence. We will study to which extent the familiarity of a viewer with a given face or a given technical diagram can beassessed given the sequence of eye fixations. Such models would have wide-ranging applications in e-learning, criminology, and other areas.
DFG Programme
Collaborative Research Centres
