mannheim.de

The automated selection of satisfying subsets from large col-lections of photos is a central challenge in multimedia re-search. Objective criteria like the depiction of persons or the photo quality are met by existing approaches. But it is difficult to know the users ’ personal interest, which plays an important role in the selection process. The expected spread of devices with eye tracking support in the near future al-lows us to measure this interest in a new way. In an exper-iment with 12 participants, we derive the most interesting photos of a collection for every person from gaze information recorded during the free viewing of the photos. We can show that the eye tracking information delivers valuable informa-tion about the users ’ preferences by comparing the results to a manual selection. The selection based on gaze information significantly outperforms baseline approaches and improves the results by up to 17%. For photo sets of personal interest this improvement is even up to 23%