Discerning Ambient/Focal Attention with Coefficient K

Author:

Krejtz Krzysztof1,Duchowski Andrew2,Krejtz Izabela1,Szarkowska Agnieszka3,Kopacz Agata4

Affiliation:

1. SWPS University of Social Sciences and Humanities, Warsaw, Poland

2. Clemson University, Clemson, SC

3. University of Warsaw, Warsaw, Poland, Warszawa, Poland

4. National Information Processing Institute, Warsaw, Poland, Niepodleglosci, Warszawa

Abstract

We introduce coefficient K , defined on a novel parametric scale, derived from processing a traditionally eye-tracked time course of eye movements. Positive and negative ordinates of K indicate focal or ambient viewing, respectively, while the abscissa serves to indicate time, so that K acts as a dynamic indicator of fluctuation between ambient/focal visual behavior. The coefficient indicates the difference between fixation duration and its subsequent saccade amplitude expressed in standard deviation units, facilitating parametric statistical testing. To validate K empirically, we test its utility by capturing ambient and focal attention during serial and parallel visual search tasks (Study 1). We then show how K quantitatively depicts the difference in scanning behaviors when attention is guided by audio description during perception of art (Study 2).

Funder

University of Warsaw

Faculty of Applied Languages

“Audio description in education”

Publisher

Association for Computing Machinery (ACM)

Subject

Experimental and Cognitive Psychology,General Computer Science,Theoretical Computer Science

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1. Differentiating Everyday Map Tasks: Unique Attention-Related Eye Movements and Electrophysiological Signatures of Map Use;Annals of the American Association of Geographers;2024-06-20

2. WatchCap: Improving Scanning Efficiency in People with Low Vision through Compensatory Head Movement Stimulation;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-05-13

3. Towards an Eye-Brain-Computer Interface: Combining Gaze with the Stimulus-Preceding Negativity for Target Selections in XR;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

4. Eye movement analysis for real-world settings using segmented linear regression;Computers in Biology and Medicine;2024-05

5. A-DisETrac Advanced Analytic Dashboard for Distributed Eye Tracking;International Journal of Multimedia Data Engineering and Management;2024-04-02

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