Locating user attention using eye tracking and EEG for spatio-temporal event selection

In expert video analysis, the selection of certain events in a continuous video stream is a frequently occurring operation, e.g., in surveillance applications. Due to the dynamic and rich visual input, the constantly high attention and the required hand-eye coordination for mouse interaction, this is a very demanding and exhausting task. Hence, relevant events might be missed. We propose to use eye tracking and electroencephalography (EEG) as additional input modalities for event selection. From eye tracking, we derive the spatial location of a perceived event and from patterns in the EEG signal we derive its temporal location within the video stream. This reduces the amount of the required active user input in the selection process, and thus has the potential to reduce the user's workload. In this paper, we describe the employed methods for the localization processes and introduce the developed scenario in which we investigate the feasibility of this approach. Finally, we present and discuss results on the accuracy and the speed of the method and investigate how the modalities interact.