Catching your eyes: AI-driven modeling and analysis of eye-tracking data (ETS)2.5 ECTS
(englische Bezeichnung: Catching your eyes: AI-driven modeling and analysis of eye-tracking data)

Lehrveranstaltungen:

• • Catching your eyes: AI-driven modeling and analysis of eye-tracking data
    (Seminar, 2 SWS, Dario Zanca, Di, 12:15 - 13:45, 00.010; Organisation and slides via StudOn.)

Inhalt:

Contents Seeing is a complex activity. Humans perform eye movements to actively seek for useful information, while regulating pupil size to control the amount of light to be captured. Eye-tracking can be used to record the eye’s activity. It is a powerful tool to study human gaze behavior and it can be used to assess the health condition of individuals. The aim of this seminar is to become familiar with eye-tracking data and their use in different domains, from neuroscience and artificial intelligence (to understand and simulate human attention), to medicine and psychology (to identify eye-tracking based biomarkers). Different methods will be introduced and compared. Students will study on state-of-the-art papers and present the details of the chosen topic described in the papers. Alternatively, the student may work on experimental task and present the result of applying state of the art methods.

Lernziele und Kompetenzen:

After completing the module, students will
• be able to describe an eye-tracking experimental setup and how to work with eye-tracking data.
• be able to explain the common eye-tracking data analysis techniques.
• be able to explain the state-of-the-art saliency and scanpath models to predict human visual attention.

Literatur:

• Itti, L., Koch, C., & Niebur, E. (1998). A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on pattern analysis and machine intelligence, 20(11), 1254-1259.
• Borji, A., & Itti, L. (2012). State-of-the-art in visual attention modeling. IEEE transactions on pattern analysis and machine intelligence, 35(1), 185-207.
• Judd, T., Ehinger, K., Durand, F., & Torralba, A. (2009, September). Learning to predict where humans look. In 2009 IEEE 12th international conference on computer vision (pp. 2106-2113). IEEE.
• Zanca, D., & Gori, M. (2017, December). Variational laws of visual attention for dynamic scenes. In Proceedings of the 31st International Conference on Neural Information Processing Systems (pp. 3826-3835).
• Zanca, D., Melacci, S., & Gori, M. (2019). Gravitational laws of focus of attention. IEEE transactions on pattern analysis and machine intelligence, 42(12), 2983-2995.
• Zanca, D., Gori, M., Melacci, S., & Rufa, A. (2020). Gravitational models explain shifts on human visual attention. Scientific Reports, 10(1), 1-9.
• Bellet, M. E., Bellet, J., Nienborg, H., Hafed, Z. M., & Berens, P. (2019). Human-level saccade detection performance using deep neural networks. Journal of neurophysiology, 121(2), 646-661.
• Piu, P., Serchi, V., Rosini, F., & Rufa, A. (2019). A cross-recurrence analysis of the pupil size fluctuations in steady scotopic conditions. Frontiers in neuroscience, 13, 407.
• Zénon, A. (2017). Time-domain analysis for extracting fast-paced pupil responses. Scientific reports, 7(1), 1-10.
• Bargagli, A., Fontanelli, E., Zanca, D., Castelli, I., Rosini, F., Maddii, S., ... & Rufa, A. (2020). Neurophthalmologic and Orthoptic Ambulatory Assessments Reveal Ocular and Visual Changes in Patients With Early Alzheimer and Parkinson's Disease. Frontiers in Neurology, 11.

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:
Das Modul ist im Kontext der folgenden Studienfächer/Vertiefungsrichtungen verwendbar:

1. Artificial Intelligence (Master of Science)
   (Po-Vers. 2021s | TechFak | Artificial Intelligence (Master of Science) | Gesamtkonto | Hauptseminar | Catching your eyes: AI-driven modeling and analysis of eye-tracking data)
2. Informatik (Master of Science)
   (Po-Vers. 2010 | TechFak | Informatik (Master of Science) | Gesamtkonto | Nebenfach | Nebenfach Artificial Intelligence in Biomedical Engineering | Catching your eyes: AI-driven modeling and analysis of eye-tracking data)
3. Medizintechnik (Master of Science)
   (Po-Vers. 2018w | TechFak | Medizintechnik (Master of Science) | M4 Hauptseminar Medizintechnik | Catching your eyes: AI-driven modeling and analysis of eye-tracking data)
4. Medizintechnik (Master of Science)
   (Po-Vers. 2019w | TechFak | Medizintechnik (Master of Science) | Modulgruppe M4 - Hauptseminar | Hauptseminar Medizintechnik / Advanced Seminar Medical Engineering | Catching your eyes: AI-driven modeling and analysis of eye-tracking data)

Studien-/Prüfungsleistungen:

Catching your eyes: AI-driven modeling and analysis of eye-tracking data (Prüfungsnummer: 76131)

Prüfungsleistung, Seminarleistung, Dauer (in Minuten): 30, benotet, 2.5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

weitere Erläuterungen:
presentation (50%) and written report (50%)

Erstablegung: SS 2022, 1. Wdh.: WS 2022/2023 (nur für Wiederholer)

1. Prüfer:

Björn Eskofier