Name
Abstract | ||
|---|---|---|
Smooth pursuit eye movements provide meaningful insights and information on subject's behavior and health and may, in particular situations, disturb the performance of typical fixation/saccade classification algorithms. Thus, an automatic and efficient algorithm to identify these eye movements is paramount for eye-tracking research involving dynamic stimuli. In this paper, we propose the Bayesian Decision Theory Identification (I-BDT) algorithm, a novel algorithm for ternary classification of eye movements that is able to reliably separate fixations, saccades, and smooth pursuits in an online fashion, even for low-resolution eye trackers. The proposed algorithm is evaluated on four datasets with distinct mixtures of eye movements, including fixations, saccades, as well as straight and circular smooth pursuits; data was collected with a sample rate of 30 Hz from six subjects, totaling 24 evaluation datasets. The algorithm exhibits high and consistent performance across all datasets and movements relative to a manual annotation by a domain expert (recall: μ = 91.42%, σ = 9.52%; precision: μ = 95.60%, σ = 5.29%; specificity μ = 95.41%, σ = 7.02%) and displays a significant improvement when compared to I-VDT, an state-of-the-art algorithm (recall: μ = 87.67%, σ = 14.73%; precision: μ = 89.57%, σ = 8.05%; specificity μ = 92.10%, σ = 11.21%). Algorithm implementation and annotated datasets are openly available at www.ti.uni-tuebingen.de/perception
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Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2857491.2857512 | arXiv: Computer Vision and Pattern Recognition |
Keywords | Field | DocType |
smooth pursuit, eye-tracking, probabilistic, model, online, classification, dynamic stimuli, open-source | Smooth pursuit,Computer vision,Fixation (psychology),Computer science,Eye tracking,Eye movement,Artificial intelligence,Statistical classification,Saccade,Bayes estimator,Bayesian probability | Journal |
Volume | ISBN | Citations |
abs/1511.07732 | 978-1-4503-4125-7 | 15 |
PageRank | References | Authors |
0.65 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| thiago santini | 1 | 63 | 8.72 |
| wolfgang fuhl | 2 | 123 | 11.95 |
| Thomas C. Kübler | 3 | 124 | 12.57 |
| Enkelejda Kasneci | 4 | 202 | 33.86 |