Skeleton-based motion prediction: A survey - Usman, Muhammad; Zhong, Jianqi (Frontiers in Computational Neuroscience, 2022)
Human motion prediction based on 3D skeleton data is an active research topic in computer vision and multimedia analysis, which involves many disciplines, such as image processing, pattern recognition, and artificial intelligence. As an effective representation of human motion, human 3D skeleton data is favored by researchers because it is not easily affected by light, scene changes, etc. Previous research on human motion prediction mainly focused on RGB data-based methods. In recent years, researchers have proposed the fusion of human skeleton data and depth learning methods for human motion prediction and achieved good results. We first introduced human motion prediction's research background and significance in this survey. We then summarized the latest deep learning-based methods for human motion prediction in recent years. Finally, a detailed paper review and future development discussion are provided.