Evaluating movement qualities with visual feedback for real-time motion capture

Aishah Hussain, Camilla Mødekjær, Nicoline Warming Austad, Sofia Dahl, Cumhur Erkut

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)
58 Downloads (Pure)

Abstract

The focus of this paper is to investigate how the design of visual feedback on full body movement affects the quality of the movements. Informed by the theory of embodiment in interaction design and media technology, as well as by the Laban theory of effort, a computer application was implemented in which users are able to project their movements onto two visuals ('Particle' and 'Metal') We investigated whether the visual designs influenced movers through an experiment where participants were randomly assigned to one of the visuals while performing a set of simple tasks. Qualitative analysis of participants' verbal movement descriptions as well as analysis of quantitative movement features combine several perspectives with respect to describing the differences and the change in the movement qualities. The qualitative data shows clear differences between the groups. The quantitative data indicates that all groups move differently when visual feedback is provided. Our results contribute to the design effort of visual modality in movement-focused design of extended realities.

Original languageEnglish
Title of host publicationMOCO 2019 - Proceedings of the 6th International Conference on Movement and Computing
PublisherAssociation for Computing Machinery
Publication date10 Oct 2019
Article numbera1
ISBN (Electronic)978-1-4503-7654-9
DOIs
Publication statusPublished - 10 Oct 2019
Event6th International Conference for Movement and Computing, MOCO 2019 - Tempe, United States
Duration: 10 Oct 201912 Oct 2019

Conference

Conference6th International Conference for Movement and Computing, MOCO 2019
Country/TerritoryUnited States
CityTempe
Period10/10/201912/10/2019

Keywords

  • Embodied interaction
  • Motion capture
  • Visualization models

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