EyeSee3D 2.0: model-based real-time analysis of mobile eye-tracking in static and dynamic three-dimensional scenes

With the launch of ultra-portable systems, mobile eye tracking finally has the potential to become mainstream. While eye movements on their own can already be used to identify human activities, such as reading or walking, linking eye movements to objects in the environment provides even deeper insights into human cognitive processing. We present a model-based approach for the identification of fixated objects in three-dimensional environments. For evaluation, we compare the automatic labelling of fixations with those performed by human annotators. In addition to that, we show how the approach can be extended to support moving targets, such as individual limbs or faces of human interaction partners. The approach also scales to studies using multiple mobile eye-tracking systems in parallel. The developed system supports real-time attentive systems that make use of eye tracking as means for indirect or direct humancomputer interaction as well as off-line analysis for basic research purposes and usability studies.