Skip to main content
eScholarship
Open Access Publications from the University of California

Understanding Individual Differences in Eye Movement Pattern During ScenePerception through Co-Clustering of Hidden Markov Models

Abstract

Here we combined the Eye Movement analysis with Hidden Markov Models (EMHMM) method with the data miningtechnique co-clustering to discover participant groups with consistent eye movement patterns across stimuli during sceneperception. We discovered explorative (switching between foreground and background information) and focused (mainlyon foreground) eye movement strategy groups among Asian participants. In contrast to previous research suggesting acultural difference where Asians adopted explorative and Caucasians used focused eye movement strategies, we foundthat explorative patterns were associated with better foreground object recognition performance whereas focused patternswere associated with better feature integration in the flanker task and higher preference rating of the scenes. In addition,images with a salient foreground object relative to the background induced larger individual differences in eye movements.Thus, eye movements in scene perception not only contribute to scene recognition performance, but also reflects individualdifferences in cognitive ability and scene preference.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View