A guideline for integrating dynamic areas of interests in existing set-up for capturing eye movement: Looking at moving aircraft

Abstract

Today, capturing the behavior of a human eye is considered a standard method for measuring the information-gathering process and thereby gaining insights into cognitive processes. Due to the dynamic character of most task environments there is still a lack of a structured and automated approach for analyzing eye movement in combination with moving objects. In this article, we present a guideline for advanced gaze analysis, called IGDAI (Integration Guideline for Dynamic Areas of Interest). The application of IGDAI allows gathering dynamic areas of interest and simplifies its combination with eye movement. The first step of IGDAI defines the basic requirements for the experimental setup including the embedding of an eye tracker. The second step covers the issue of storing the information of task environments for the dynamic AOI analysis. Implementation examples in XML are presented fulfilling the requirements for most dynamic task environments. The last step includes algorithms to combine the captured eye movement and the dynamic areas of interest. A verification study was conducted, presenting an air traffic controller environment to participants. The participants had to distinguish between different types of dynamic objects. The results show that in comparison to static areas of interest, IGDAI allows a faster and more detailed view on the distribution of eye movement.