Eye tracking data in multimedia containers for instantaneous visualizations

Nowadays, the amount of gaze data records of subjects associated with video sequences increases daily. These eye tracking data are unfortunately stored in separate files in custom-made data formats, which reduces accessibility even for experts and makes the data effectively inaccessible for non-experts. Consequently, we still lack interfaces for many common use cases, such as visualization, streaming, data analysis, high level understanding, and semantic web integration of eye tracking data. To overcome these shortcomings, we want to promote the use of existing multimedia container formats to establish a standardized method of incorporating content videos with eye tracking metadata. This will facilitate instantaneous visualization in standard multimedia players, streaming via the Internet, and easy usage without conversion. Using our prototype software, we embed gaze data from eye tracking studies and the corresponding video into a single multimedia container, which can be visualized by any media player. Based on this prototype implementation, we discuss the benefit of our approach as a possible standard for storing eye tracking metadata including the corresponding video.