SubsMatch: scanpath similarity in dynamic scenes based on subsequence frequencies

Abstract

The analysis of visual scanpaths, i.e., series of fixations and saccades, in complex dynamic scenarios is highly challenging and usually performed manually. We propose SubsMatch, a scanpath comparison algorithm for dynamic, interactive scenarios based on the frequency of repeated gaze patterns. Instead of measuring the gaze duration towards a semantic target object (which would be hard to label in dynamic scenes), we examine the frequency of attention shifts and exploratory eye movements. SubsMatch was evaluated on highly dynamic data from a driving experiment to identify differences between scanpaths of subjects who failed a driving test and subjects who passed.