Dancing robots: aesthetic engagement is shaped by stimulus and knowledge cues to human animacy
These findings provide insights into the design of robotic dance, highlighting features of dance choreography and audience characteristics that influence aesthetic engagement. To enhance AI-driven creative productions, shaping perceptions will be crucial for better audience reception and engagement.
Authors
- Emily S. Cross (ORCID: https://orcid.org/0000-0002-1671-5698)
- Kohinoor Monish Darda (ORCID: https://orcid.org/0000-0002-2692-7360)
- Tanvi Raghuram (ORCID: https://orcid.org/0000-0001-5475-9109)
- Aaron Maiwald
Institutions
- Osnabrück University (DE)
- ETH Zurich (CH)
Publication Details
- Journal
- Frontiers in Human Neuroscience
- Published
- 2024-11-25
- DOI
- https://doi.org/10.3389/fnhum.2024.1413066
- Citations
- 1
- Primary Topic
- Action Observation and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 0.64
Funders
- Leverhulme Trust
- Eidgenössische Technische Hochschule Zürich