Suggesting Gaze-based Selection for Surveillance Applications

Abstract

The selection operation is a basic input operation when interacting with a computer. Traditional manual selection methods like mouse input are challenging when interacting with a dynamic scene containing moving objects as it occurs in surveillance applications. In this contribution, we give an overview on gaze-based selection as a fast and intuitive alternative method considering typical selection tasks in surveillance applications. In this context, we report the results of an evaluation on initialization of an object-tracking algorithm performed by eighteen expert video analysts. Besides its benefits, gaze-based selection is difficult if selection objects are small and close together. We provide first results of a pilot study evaluating a distance measure, which might have the potential of making gaze-based selection more robust. Finally, to leverage gaze-based selection becoming a common technique, low-cost eye-tracking devices have to be available which achieve the same accuracy as the high-end devices. As such cheap eye-trackers only recently became available, it is so far not evident, which accuracy we can expect. Hence, we report the results of an accuracy evaluation of the Tobii 4C conducted with twelve students performing a calibration-style task.