TY - CPAPER SN - 978-1-4503-6709-7 AU - Kumar, Ayush AU - Timmermans, Neil AU - Burch, Michael AU - Müller, Klaus T1 - Clustered eye movement similarity matrices T2 - Symposium on Eye Tracking Research and Applications PY - 2019 CY - New York PB - Association for Computing Machinery (ACM) UR - ttps://doi.org/10.1145/3317958.3319811 SP - 82:1 EP - 82:9 AB - Eye movements recorded for many study participants are difficult to interpret, in particular when the task is to identify similar scanning strategies over space, time, and participants. In this paper we describe an approach in which we first compare scanpaths, not only based on Jaccard (JD) and bounding box (BB) similarities, but also on more complex approaches like longest common subsequence (LCS), Frechet distance (FD), dynamic time warping (DTW), and edit distance (ED). The results of these algorithms generate a weighted comparison matrix while each entry encodes the pairwise participant scanpath comparison strength. To better identify participant groups of similar eye movement behavior we reorder this matrix by hierarchical clustering, optimal-leaf ordering, dimensionality reduction, or a spectral approach. The matrix visualization is linked to the original stimulus overplotted with visual attention maps and gaze plots on which typical interactions like temporal, spatial, or participant-based filtering can be applied. Y3 - 09.09.2021 C7 - ETRA 2019 C1 - Denver, 25. - 28. Juni M4 - Citavi ER -