Automatic Generation of Customized AOIs and Evaluation of Observers' Gaze in Portrait Videos

We present a novel framework for the evaluation of eye tracking data in portrait videos including the automatic generation of customized areas of interest (AOIs) based on facial landmarks. In contrast to previous work, our framework allows the user to flexibly create AOIs by grouping the detected landmarks. Moreover, their shape and size can be modified to better fit both the research question and the precision of the eye tracker. The framework can be used as an integrated solution to not only generate AOIs but also to evaluate viewing behavior like the overall fixation times, the similarity of scanpaths, and the number of saccades between AOIs. Other functionalities include the visualization of gaze paths and the creation of heatmaps. We demonstrate the benefits of our framework and user-defined AOI layouts via an exemplary application, i.e., the investigation of face swapping artifacts.