Abstract
How the classification of expressive movement data and use of such classifications may be used to inform the development of a knowledge-based system of movement analysis. In this paper, we present an example that adopts a practice-led design approach to the creation of immersive animation environments that features a method of indexing dance movement used by artists and designers to characterize this movement using “narrative grammar” based on pathemic, kinesthetic, cinematographic and aesthetic criteria referred to as a “movement index”. The utility of the system described in this experiment was tested principally in art and design but this use can be generalized, to inform the development of cognitive medical applications for analyzing irregular movement patterns or the unusual motion behavior often characteristic of the ill or the elderly.
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Notes
- 1.
It is beyond the scope of this paper to expand on this large body of knowledge that includes key thinkers in the area of dance movement such as Rudolf Laban’s Labanotation published in 1928 and works of the early pioneers of abstract animation such as Viking Eggling’s Symphonie Diagonale (1924) or Osckar Fishinger’s Motion Painting No.1 (1947).
- 2.
Practice led research are approaches used by artists in order to gain new knowledge and the outcomes of that practice are the finished artwork or, in this case, animation assets [2].
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Acknowledgements
We acknowledge the University of Technology Faculty of Design Building and Architecture, the Sydney Olympic Park Authority, Dean Walsh, the Hochschule Kaiserslautern College and University, Ben Simons and Darren Lee of the UTS Data Arena and the tranSTURM artist collective.
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Bowman, C., Fujita, H., Perin, G. (2016). Towards a Knowledge Based Environment for the Cognitive Understanding and Creation of Immersive Visualization of Expressive Human Movement Data. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_16
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DOI: https://doi.org/10.1007/978-3-319-42007-3_16
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