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Designing glitch procedures and visualisation workflows for markerless live motion capture of contemporary dance

Designing glitch procedures and visualisation workflows for markerless live motion capture of contemporary dance

Jürgens, Stephan, Correia, Nuno N. ORCID: 0000-0002-9999-9162 and Masu, Raul (2020) Designing glitch procedures and visualisation workflows for markerless live motion capture of contemporary dance. In: MOCO '20: Proceedings of the 7th International Conference on Movement and Computing. ACM, Jersey City, NJ, USA, pp. 1-8. ISBN 978-1450375054 (doi:https://doi.org/10.1145/3401956.3404225)

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Abstract

This paper presents a case study in the exploration and creative usage of errors and glitches in the real-time markerless motion capture of contemporary dance. We developed a typology of MoCap failures comprised of seven categories, allowing the user to situate each distinct error in the respective stage of the motion capture pipeline. This way, glitch procedures for the creative use of ‘bad’ MoCap data were designed, resulting in uncommon avatar visualisations. We propose an additional ‘re-visualisation’ module in our motion capture pipeline and avatar staging approach, which enables choreographers and digital artists to rapidly prototype their ideas in a mixed reality performance environment. Finally, we discuss how our extended MoCap pipeline and avatar staging set-up can support artists and researchers who aim at a flexible and adaptive workflow in real-time motion visualization.

Item Type: Conference Proceedings
Title of Proceedings: MOCO '20: Proceedings of the 7th International Conference on Movement and Computing
Additional Information: MOCO ’20 was held from July 15–17, 2020, Jersey City/Virtual, NJ, USA.
Uncontrolled Keywords: Motion capture, glitch, digital error, markerless, live visuals, contemporary dance, mixed reality set-up, visualisation, choreography
Subjects: N Fine Arts > N Visual arts (General) For photography, see TR
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > School of Computing and Mathematical Sciences
Related URLs:
Last Modified: 03 Aug 2020 09:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/28451

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