Application of motion capture technology based on dance big data in dance retrieval

[1] Aristidou, A., Shamir, A., & Chrysanthou, Y. (2019). Digital dance ethnography: Organizing large dance collections. Journal on Computing and Cultural Heritage (JOCCH), 12(4), 1-27. Search in Google Scholar

[2] Gold, L. T. (2017). Dance motion capture and synthesis using multiple RGB and depth sensors. International Journal of Distributed Sensor Networks, 13(2), 155014771769608. Search in Google Scholar

[3] Li, Y. (2021). Dance motion capture based on data fusion algorithm and wearable sensor network. Complexity, 2021(1), 1-11. Search in Google Scholar

[4] Voulodimos, A., Rallis, I., & Doulamis, N. (2020). Physics-based keyframe selection for human motion summarization. Multimedia Tools and Applications, 79(5), 3243-3259. Search in Google Scholar

[5] Shang, M. (2021). Reflections on the reform of dance teaching in higher vocational colleges based on big data. Journal of Physics: Conference Series, 1852(2), 022084 (7pp). Search in Google Scholar

[6] Li, X., & Zheng, H. (2020). Object detection algorithm for dance moving images based on sensor and motion capture data. Microprocessors and Microsystems, 81(2), 103743. Search in Google Scholar

[7] Jin, Y. Z. (2017). Dance motion capture and synthesis using multiple RGB and depth sensors. International Journal of Distributed Sensor Networks, 13(2), 155014771769608. Search in Google Scholar

[8] Kico, I., Grammalidis, N., Christidis, Y., & Liarokapis, F. (2018). Digitization and visualization of folk dances in cultural heritage: A review. Inventions, 3(4), 72. Search in Google Scholar

[9] Kim, Y., Bai, S., & Pei, B. C. (2017). Human motion capture with multiple depth sensors. Etri Magazine, 39(2), 181-190. Search in Google Scholar

[10] Li, Y. (2021). Dance motion capture based on data fusion algorithm and wearable sensor network. Complexity, 2021(1), 1-11. Search in Google Scholar

[11] Aksoy, D. A. (2020). Finding a Home for Every Imaging Dataset. Nature, 579(7797), 162-163. Search in Google Scholar

[12] Sarki, R., Ahmed, K., Wang, H., & Zhang, Y. (2020). Automated detection of mild and multi-class diabetic eye diseases using deep learning. Health Information Science and Systems, 8(1), 1-9. Search in Google Scholar

[13] Zhuang, W., Wang, C., Chai, J., Wang, Y., Shao, M., & Xia, S. (2022). Music2dance: Dancenet for music-driven dance generation. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2), 1-21. Search in Google Scholar

[14] Chan, J. C. P., Leung, H., & Tang, J. K. T. (2011). A virtual reality dance training system using motion capture technology. Learning Technology, IEEE Transactions on, 4(2), 187-195. Search in Google Scholar

[15] Carlson, E., Saari, P., Burger, B., & Toiviainen, P. (2020). Dance to your own drum: Identification of musical genre and individual dancer from motion capture using machine learning. Journal of New Music Research, 49(2), 162-177. Search in Google Scholar

[16] Simpson, T. T., Wisner, S. L., & Bennett, B. C. (2014). Dance recognition system based on lower limb movements. Journal of Applied Biomechanics, 30(1), 147-153. Search in Google Scholar

[17] Gao, Y., & Xu, D. (2021). Application of gesture recognition service system based on information fusion intelligent sensor in dance training. Sensors Journal, 2021(4), 1-7. Search in Google Scholar

[18] Li, Y. (2021). Dance motion capture based on data fusion algorithm and wearable sensor network. Complexity, 2021(1), 1-11. Search in Google Scholar

[19] Nan, S. H., & Jin, J. Y. (2018). A healthy dance exercise game system using wearable devices. IEEE Access, PP(99), 1-1. Search in Google Scholar

[20] Liu, H. (2017). Research on real-time dance pose analysis method based on feature vector matching. Boletin Tecnico/Technical Bulletin, 55(15), 321-326. Search in Google Scholar