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  Recognizing your own motions on virtual avatars: is it me or not?

Wellerdiek, A., Leyrer, M., Volkova, E., Chang, D.-S., & Mohler, B. (2013). Recognizing your own motions on virtual avatars: is it me or not?. Poster presented at ACM Symposium on Applied Perception (SAP '13), Dublin, Ireland.

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externe Referenz:
https://www.scss.tcd.ie/conferences/SAP2013/ (beliebiger Volltext)
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 Urheber:
Wellerdiek, AC1, 2, Autor           
Leyrer, M1, 2, Autor           
Volkova, E1, 2, Autor           
Chang, D-S1, 2, Autor           
Mohler, BJ1, 2, Autor           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Zusammenfassung: Most of the time point-light figures are used for motion-recognition, which present motions by only displaying the moving joints of the actor. In this study we were interested in whether self-recognition of motion changes with different representations. First, we captured participants' motions and remapped them on a point-light figure and a male and female virtual avatar. In the second part the same participants were asked to recognize their own motions on all three representations. We found that the recognition rate for own motions is high across all representations and different actions. The recognition rate was better on the point-light figure, despite being perceived as most difficult from the participants. The gender of the visual avatar did not matter in self-recognition.

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 Datum: 2013-08
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1145/2492494.2501895
 Art des Abschluß: -

Veranstaltung

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Titel: ACM Symposium on Applied Perception (SAP '13)
Veranstaltungsort: Dublin, Ireland
Start-/Enddatum: -

Entscheidung

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Titel: ACM Symposium on Applied Perception (SAP '13)
Genre der Quelle: Konferenzband
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Affiliations:
Ort, Verlag, Ausgabe: New York, NY, USA : ACM
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 138 Identifikator: ISBN: 978-1-4503-2262-1