Abstract. Metadata describing the content of photos are of high importance for applications like image search or as part of training sets for object detection algorithms. In this work, we apply tags to image regions for a more detailed description of the photo semantics. This region labeling is performed without additional effort from the user, just from analyzing eye tracking data, recorded while users are playing a gazecontrolled game. In the game EyeGrab, users classify and rate photos falling down the screen. The photos are classified according to a given category under time pressure. The game has been evaluated in a study with 54 subjects. The results show that it is possible to assign the given categories to image regions with a precision of up to 61%. This shows that we can perform an almost equally good region labeling using an immersive environment like in EyeGrab compared to a previous classification experiment that was much more controlled.
We have presented the game EyeGrab REF , with the same goal of image region labeling, but performed in a gaze-controlled game for single users.
Exploitation of Gaze Data for Photo Region Labeling in an Immersive Environment
MMM
Computer Science