Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
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Proceedings of the Symposium on Eye Tracking Research and Applications
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Proceedings of the Symposium on Eye Tracking Research and Applications
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Proceedings of the Symposium on Eye Tracking Research and Applications
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The scanpath comparison framework based on string editing is revisited. The previous method of clustering based on k-means "preevaluation" is replaced by the mean shift algorithm followed by elliptical modeling via Principal Components Analysis. Ellipse intersection determines cluster overlap, with fast nearest-neighbor search provided by the kd-tree. Subsequent construction of Y - matrices and parsing diagrams is fully automated, obviating prior interactive steps. Empirical validation is performed via analysis of eye movements collected during a variant of the Trail Making Test, where participants were asked to visually connect alphanumeric targets (letters and numbers). The observed repetitive position similarity index matches previously published results, providing ongoing support for the scanpath theory (at least in this situation). Task dependence of eye movements may be indicated by the global position index, which differs considerably from past results based on free viewing.