Design and Implementation of Dance Motion Capture System Based on Deep Learning Algorithm

This paper is devoted to the design and implementation of a dance motion capture system based on deep learning algorithm, aiming at improving the accuracy and real-time performance of dancers' motion capture. By introducing advanced deep learning technology, especially the Mask R-CNN algorithm,...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2023 International Conference on Internet of Things, Robotics and Distributed Computing (ICIRDC) s. 153 - 157
Hlavní autor: Wang, Xinxiu
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 29.12.2023
Témata:
Dance Motion
Deep learning
Humanities
Mask R-CNN
Motion capture
Technological innovation
Three-dimensional displays
Training
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper is devoted to the design and implementation of a dance motion capture system based on deep learning algorithm, aiming at improving the accuracy and real-time performance of dancers' motion capture. By introducing advanced deep learning technology, especially the Mask R-CNN algorithm, we successfully solved the common problems of complex posture and occlusion in traditional dance motion capture systems. The system can accurately capture the movements of various parts of the dancer's body, and restore the dance movements in 3D space, which provides a more accurate expression and creation platform for dancers. By optimizing the algorithm and hardware, we realized the real-time capture and analysis of different dance styles and action types, which provided a more flexible and diverse training and performance environment for dancers. This study provides strong support for the development of dance motion capture technology, provides advanced and practical tools for dancers, educators and researchers, and promotes the innovation and progress of dance art.
DOI:10.1109/ICIRDC62824.2023.00033