Skilled gaze behavior extraction based on dependency analysis of gaze patterns on video scenes
نویسندگان
چکیده
The eye gaze behavior of individuals changes depending on their knowledge and experience of the event occurring in their field of view. In past studies, researchers formulated a hypothesis concerning this dependency on a specific scene and then analyzed the gaze behavior of viewers observing the scene. We depart from this hypothesis-testing paradigm. In this paper, we propose a datamining framework for extracting skilled gaze behaviors of experts while watching a video based on a comprehensive comparison of viewers in terms of the dependency of their gaze patterns on video scenes. To quantitatively analyze the changes in the gaze behavior of experts according to the events in the scene, video and eye movement sequences are classified into video scenes and gaze patterns, respectively, by using an unsupervised clustering method focusing on short-time dynamics. Then, we analyze the dependency based on the distinctiveness and occurrence frequency of gaze patterns for each video scene.
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