Year: 2025
Type: article
Abstract: Motion capture technology is a crucial digital animation production method in the fields of film and television and games. Unmarked motion capture technology has received increasing attention and wide application in recent years due to its ability to significantly reduce the time for data collection and processing. However, this technology is prone to generating incorrect human posture information when dealing with occlusion issues. Therefore, this paper attempts to combine Long Short-Term Memory networks (LSTM) for human posture prediction to correct or eliminate incorrect posture data, thereby enhancing the accuracy and reliability of motion capture.
DOI: 10.61173/4vyed650
Author: Qiang Zhou
Language: English
Topic: Human Motion and Animation
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409620877