Abstract
The investigation of human signals has been a topic of research since the advent of technology enabled their acquisition. Signals like gaze can reveal part of the human brain mechanisms. To facilitate the research of the analysis of these signals, researchers are developing and publishing datasets. This paper introduces the Augmented Reality DISTraction dataset (ARDIST), a novel dataset for processing human gaze. The primary objective of this dataset is to provide the scientific community with a resource that researchers can use to assess the distraction/attention levels of individuals performing specific tasks in the Robotic environment. The experiment was designed based on the latest findings in the field of neuroscience to include a diverse range of variables that affect human attention levels. Furthermore, the dataset can be utilized to model the human gaze signal under the influence of significant factors.
The work presented in this paper was supported by the European Commission under contract H2020 - 101016953 CoRoSect.
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Zaparas, P., Katranitsiotis, P., Stavridis, K., Daras, P. (2023). Detecting Human Distraction from Gaze: An Augmented Reality Approach in the Robotic Environment. In: Meder, F., Hunt, A., Margheri, L., Mura, A., Mazzolai, B. (eds) Biomimetic and Biohybrid Systems. Living Machines 2023. Lecture Notes in Computer Science(), vol 14157. Springer, Cham. https://doi.org/10.1007/978-3-031-38857-6_4
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