Proceedings Article10.1145/355017.355028
Identifying fixations and saccades in eye-tracking protocols
Dario D. Salvucci,Joseph H. Goldberg +1 more
- 08 Nov 2000
- pp 71-78
TL;DR: A taxonomy of fixation identification algorithms is proposed that classifies algorithms in terms of how they utilize spatial and temporal information in eye-tracking protocols in order to evaluate and compare these algorithms with respect to a number of qualitative characteristics.
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Abstract: The process of fixation identification—separating and labeling fixations and saccades in eye-tracking protocols—is an essential part of eye-movement data analysis and can have a dramatic impact on higher-level analyses. However, algorithms for performing fixation identification are often described informally and rarely compared in a meaningful way. In this paper we propose a taxonomy of fixation identification algorithms that classifies algorithms in terms of how they utilize spatial and temporal information in eye-tracking protocols. Using this taxonomy, we describe five algorithms that are representative of different classes in the taxonomy and are based on commonly employed techniques. We then evaluate and compare these algorithms with respect to a number of qualitative characteristics. The results of these comparisons offer interesting implications for the use of the various algorithms in future work.
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Citations
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Unsupervised parsing of gaze data with a beta-process vector auto-regressive hidden Markov model
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Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks
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- 23 Oct 2016
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Nora Castner,Solveig Klepper,Lena Kopnarski,Fabian Hüttig,Constanze Keutel,Katharina Scheiter,Juliane Richter,Thérése Eder,Enkelejda Kasneci +8 more
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