Three-Dimensional Animation Capture Driver Technology for Digital Media

Abstract: For the motion capture driving technology of three-dimensional animation, this study combines skeleton extraction methods and human motion pose data to construct the human skeleton of three-dimensional animated characters. Combining matching algorithms and action recognition techniques, the postures of the human three-dimensional model were tested and analyzed. The experimental results showed that the level-set central clustering method extracted shoulder joint position values of 0.26, 0.24, 0.28, and 0.21 in the four models, respectively. The error value was the smallest among the skeleton extraction algorithms, indicating that this skeleton extraction algorithm had high accuracy in extracting human skeleton information. In addition, the depth information of human joint points was compared using the parallax ranging method, and the highest error was 1.57%. This further demonstrated that the coordinate error of the three-dimensional joints was relatively accurate, which also proved the effectiveness of the binocular stereo vision system. The system had an accuracy of over 80% in recognizing joint rotation information and dynamic movements in the human three-dimensional model. Finally, the highest accuracy of inertial sensors in capturing human movements was 97%, indicating the superiority of digital media in capturing three-dimensional animation technology. This also provides a theoretical basis and technical reference for animation production and other aspects.

Wanjie Dong. “Three-Dimensional Animation Capture Driver Technology for Digital Media”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.6 (2024). http://dx.doi.org/10.14569/IJACSA.2024.01506108

@article{Dong2024,
title = {Three-Dimensional Animation Capture Driver Technology for Digital Media},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01506108},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01506108},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {6},
author = {Wanjie Dong}
}