Towards accurate and practical predictive models of active-vision-based visual search.

Being able to predict the performance of interface designs using models of human cognition and performance is a long-standing goal of HCI research. This paper presents recent advances in cognitive modeling which permit increasingly realistic and accurate predictions for visual human-computer interaction tasks such as icon search by incorporating an "active vision" approach which emphasizes eye movements to visual features based on the availability of features in relationship to the point of gaze. A high fidelity model of a classic visual search task demonstrates the value of incorporating visual acuity functions into models of visual performance. The features captured by the high-fidelity model are then used to formulate a model simple enough for practical use, which is then implemented in an easy-to-use GLEAN modeling tool. Easy-to-use predictive models for complex visual search are thus feasible and should be further developed.