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Modelling and Data Analysis
2020. Vol. 10, no. 2, 74–92
doi:10.17759/mda.2020100206
ISSN: 2219-3758 / 2311-9454 (online)

Assessment of Bayesian Ternary Gaze Classification Algorithm (I-BDT)

81

I.Y. Zherdev

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Abstract

I-BDT eyetracking data ternary classification (fixations, saccades, smooth pursuit) algorithm is investigated. Comparison with well-known Identification / Dispersion Threshold (I-DT) algorithm is held (accuracy, precision, recall, F1 measure). A novel approach for additionally filtering the algorithm output by distance/amplitude, area of convex hull is described.

General Information

Keywords: smooth pursuit, classification, Bayesian decision theory, eye movements

Journal rubric: Software

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100206

For citation: Zherdev I.Y. Assessment of Bayesian Ternary Gaze Classification Algorithm (I-BDT). Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2020. Vol. 10, no. 2, pp. 74–92. DOI: 10.17759/mda.2020100206. (In Russ., аbstr. in Engl.)

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Information About the Authors

Ivan Y. Zherdev, associated researcher, software developer, Moscow State University of Psychology & Education, Moscow, Russia, ORCID: https://orcid.org/0000-0001-6810-9297, e-mail: ivan866@mail.ru

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