Traditional dance is China's national intangible cultural heritage and is a precious cultural treasure of the Chinese nation. Motion capture technology (Mocap) is a hot research topic in the digital field in recent years, covering the digital fields of physical animation, gait analysis and biomechanics. This paper briefly explains the principle of optical motion capture technology, explores the technical characteristics of motion capture technology, analyzes the advantages of optical motion capture technology in realizing the digital production of traditional dance in combination with the current situation and problems of traditional dance, and designs a technical route for digital production of traditional dance based on motion capture technology. The route is applied to an example production to verify its effectiveness and feasibility.

Mengjie Wang, Riji Yu. Digital production and realization for traditional dance movements based on Motion Capture Technology. The Frontiers of Society, Science and Technology (2022) Vol. 4, Issue 11: 13-18. https://doi.org/10.25236/FSST.2022.041102.

[1] Ran Ji. Human motion capture and control based on inertial sensors [D]. Huazhong University of Science and Technology, 2017. 

[2] Ye Yuanzhi. Research on the digitization method of Tibetan pot dance based on motion capture technology [J]. China New Communication, 2020, 22(19):235-236.

[3] Xu Jing. Exploration on the inheritance of intangible cultural heritage in the teaching of ethnic folk dance in colleges and universities [J]. The House of Drama, 2018(35):214.

[4] Fei Shi-Long. Motion capture-based motion generation framework for humanoid robots [D]. Tsinghua University,2011.

[5] Jin Juan. Investigation and Research on the Tujia Gus Dance in Shuangfeng Village, Xiangxi Province [D]. China Academy of Arts, 2009.

[6] Yu Riji. Research on the digital development of intangible cultural heritage based on AR technology [D]. Wuhan: Wuhan University, 2014

[7] Du Shang. Online motion capture system for upper limbs based on MA and 5DT gloves [D]. Zhejiang University,2017.

[8] Zhang YQ. Research on facial motion capture technology based on sparse representation and cascade regression [D]. Harbin Institute of Technology, 2018. DOI: 10. 27061/ d. cnki. ghgdu. 2018. 000215. 

[9] Wang Luchen. Research on dance gesture analysis and teaching method based on motion capture technology [D]. Liaoning Normal University, 2016.

[10] Dacko S G. Enabling smart retail settings via mobile augmented reality shopping apps [J]. Technological Forecasting and Social Change, 2017.

[11] LOWE D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2):91-110.