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Browsing by Author "Endres, Dominik"

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    Eyetracking data during observation of movement primitive generated motion
    Knopp, Benjamin; Auras, Daniel; Schütz, Alexander, C.; Endres, Dominik
    We investigated gaze direction during movement observation. The eye movement data were collected during an experiment, in which different models of movement production (based on movement primitives, MPs) were compared in a two alternatives forced choice task (2AFC). In each trial, participants observed side-by-side presentation of two naturalistic 3D-rendered human movement videos, where one video was based on motion captured gait sequence, the other one was generated by recombining the machine-learned MPs to approximate the same movement. The participants' task was to discriminate between these movements while their eye movements were recorded. We are complementing previous binary decision data analyses with eye tracking data. Here, we are investigating the role of gaze direction during task execution. We computed how much information is shared between gaze features extracted from eye tracking data and decisions of the participants, and between gaze features and correct answers. We found that eye movements reflect the decision of participants during the 2AFC task, but not the correct answer. This result is important for future experiments (possibly in virtual reality), which should take advantage of eye tracking to complement binary decision data.
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    Publication
    TAM DataHub User Manual
    Lenze, Stefan; Pfarr, Julia-Katharina; Berger, Christian; Pietsch Andre; Brand, Ortrun; Endres, Dominik
    The DataHub is an infrastructure project of the "The Adaptive Mind" (TAM) cluster initiative in which research groups in the field of psychology and neuroscience, based at multiple hessian universities work together. Guided by the "FAIR" principles, the DataHub offers resources, services and support to affiliated researches on various levels to ease collaborative work: Central storage and compute resources, services like JupyterHub, TAM GitLab and the TAM DataHub Repository, which allow efficient usage of these resources, and support on how to use the services in a way that fits the needs of the individual project. In this manual, you will find an overview on the DataHub, introductions to individual resources and services and workflows to help you using the DataHub.