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Movement Quality Visualization for Wheelchair Dance

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Manage episode 443660549 series 3605621
Inhalt bereitgestellt von Kai Kunze. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Kai Kunze oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Wheelchair dance is an important form of disability art that is still subject to significant levels of ableism and art exclusion. Wheelchair dancers face challenges finding teachers and choreographers who can accommodate their needs, documenting and sharing choreographies that suit their body shapes and their assistive technologies. In turn, this hinders their ability to share creative expressions. Accessible resources and communication tools could help address these challenges. The goal of this research is the development of a visualization system grounded on Laban Movement Analysis (LMA) that notates movement quality while opening new horizons on perceptions of disabled bodies and the artistic legitimacy of wheelchair dance. The system uses video to identify the body landmarks of the dancer and wheelchair and extracts key features to create visualizations of expressive qualities from LMA basic effort. The current evaluation includes a pilot study with the general public and an online questionnaire targeting professionals to gain feedback supporting practical implementation and real-world deployment. Results from the general public evaluation showed that the visualization was effective in conveying basic effort movement qualities even to a novice audience. Expert consulted via questionnaire stated that the tool could be employed for reflective evaluation, as well as performance augmentation. The LMA visualization tool can support the artistic legitimization of wheelchair dancing through education, communication, performance, and documentation.

https://dl.acm.org/doi/10.1145/3597628

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40 Episoden

Artwork
iconTeilen
 
Manage episode 443660549 series 3605621
Inhalt bereitgestellt von Kai Kunze. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Kai Kunze oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Wheelchair dance is an important form of disability art that is still subject to significant levels of ableism and art exclusion. Wheelchair dancers face challenges finding teachers and choreographers who can accommodate their needs, documenting and sharing choreographies that suit their body shapes and their assistive technologies. In turn, this hinders their ability to share creative expressions. Accessible resources and communication tools could help address these challenges. The goal of this research is the development of a visualization system grounded on Laban Movement Analysis (LMA) that notates movement quality while opening new horizons on perceptions of disabled bodies and the artistic legitimacy of wheelchair dance. The system uses video to identify the body landmarks of the dancer and wheelchair and extracts key features to create visualizations of expressive qualities from LMA basic effort. The current evaluation includes a pilot study with the general public and an online questionnaire targeting professionals to gain feedback supporting practical implementation and real-world deployment. Results from the general public evaluation showed that the visualization was effective in conveying basic effort movement qualities even to a novice audience. Expert consulted via questionnaire stated that the tool could be employed for reflective evaluation, as well as performance augmentation. The LMA visualization tool can support the artistic legitimization of wheelchair dancing through education, communication, performance, and documentation.

https://dl.acm.org/doi/10.1145/3597628

  continue reading

40 Episoden

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