Short-time AOIs-based representative scanpath identification and scanpath aggregation
He Huang1, Philipp Doebler2, Barbara Mertins2,3
1Department of Statistics, TU Dortmund University, 44227, Dortmund, Germany. he.huang@tu-dortmund.de.
Abstract:
A new algorithm to identify a representative scanpath in a sample is presented and evaluated with eye-tracking data. According to Gestalt theory, each fixation of the scanpath should be on an area of interest (AOI) of the stimuli. As with existing methods, we first identify the AOIs and then extract the fixations of the representative scanpath from the AOIs. In contrast to existing methods, we propose a new concept of short-time AOI and extract the fixations of representative scanpath from the short-time AOIs. Our method outperforms the existing methods on two publicly available datasets. Our method can be applied to arbitrary visual stimuli, including static stimuli without natural segmentation, as well as dynamic stimuli. Our method also provides a solution for issues caused by the selection of scanpath similarity.
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