Open Access

Research on the Analysis of Traditional Dance Performance Forms and Dance Movement Characteristics Based on Artificial Intelligence Technology


Cite

Otondo, F. (2018). Using mobile sound to explore spatial relationships between dance and music performance. Digital Creativity, 29(2-3), 115-128. Search in Google Scholar

Jola, C., Pollick, F. E., & Grosbras, M. H. (2017). Arousal decrease in sleeping beauty: audiences’ neurophysiological correlates to watching a narrative dance performance of two-and-a-half hours. Dance Research, 29(supplement), 378-403. Search in Google Scholar

Jin, W. (2020). Reenactment as an archive: a study on records and reenactment of dance performance. Art History, 40, 219-240. Search in Google Scholar

Alison, D. (2017). Singularities: dance in the age of performance by andrélepecki. 2016. new york: routledge. 194 pp. 18 photographs. $125.00 cloth. isbn: 9781138907706. Dance Research Journal, 49(03), 101-103. Search in Google Scholar

Jones, C. (2020). Performance history revealed: the performance databases of rambert and the royal ballet. Dance Research, 38(2), 138-148. Search in Google Scholar

Vaessen, M. J., Etienne, A., Maurizio, M., Antonio, C., & Beatrice, D. G. (2018). Computational feature analysis of body movements reveals hierarchical brain organization. Cerebral Cortex, (8), 8. Search in Google Scholar

Huang, Z. (2019). Research on the dance movement simulation based on the virtual reality technology. Basic & clinical pharmacology & toxicology, (S9), 125. Search in Google Scholar

Seo, & KyoChul. (2017). The effects of dance music jump rope exercise on pulmonary function and body mass index after music jump rope exercise in overweight adults in 20’s. Journal of Physical Therapy Science, 29(8), 1348-1351. Search in Google Scholar

Prus, D., & Zaletel, P. (2022). Body asymmetries in dancers of different dance disciplines. International Journal of Morphology, 40. Search in Google Scholar

Matsuyama, H., Aoki, S., Yonezawa, T., Hiroi, K., Kaji, K., & Kawaguchi, N. (2021). Deep learning for ballroom dance recognition: a temporal and trajectory-aware classification model with three-dimensional pose estimation and wearable sensing. IEEE sensors journal(21-22). Search in Google Scholar

Li, X., Karuppiah, M., & Shanmugam, B. (2021). Psychological perceptual analysis based on dance therapy using artificial intelligence techniques. International Journal on Artificial Intelligence Tools. Search in Google Scholar

Clarke, F., Koutedakis, Y., Wilson, M., & Wyon, M. (2019). Associations between balance ability and dance performance using field balance tests. Medical problems of performing artists, (3), 34. Search in Google Scholar

Schuh, A. (2019). Having a personal (performance) practice: dance artists’ everyday work, support, and form. Dance Research Journal, 51(01), 79-94. Search in Google Scholar

Kelting, L. (2019). The dancer from the dance: ontologies of the body in eszter salamon’s and christophe wavelet’s monuments 0.1 and 0.2. Performance Research, 24(3), 49-54. Search in Google Scholar

Dunphy, K., Lauffenburger, S., & Denning, S. (2021). Moving forwards with competence: developing industry competency standards for dance movement therapists across australasia. The Arts in psychotherapy(72-), 72. Search in Google Scholar

Zhai, X. (2021). Dance movement recognition based on feature expression and attribute mining. Complexity, 2021(21), 1-12. Search in Google Scholar

Kim, & Yejin. (2017). Dance motion capture and composition using multiple rgb and depth sensors. International Journal of Distributed Sensor Networks, 13(2), 155014771769608. Search in Google Scholar

Kristi, M., Ornella, D., Erica, H., & Danny, B. (2018). “dance therapy” as a psychotherapeutic movement intervention in parkinson’s disease. Complementary Therapies in Medicine, 40, 248-252. Search in Google Scholar

eISSN:
2444-8656
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics