Skeletal Motion

Skeletal motion analysis focuses on understanding and modeling the movement of the human skeleton, primarily for applications in activity recognition, motion prediction, and animation. Current research emphasizes developing robust and efficient models, often employing deep learning architectures like graph convolutional networks and generative adversarial networks (GANs), to address challenges such as adversarial attacks, motion in-betweening, and accurate representation of complex interactions. These advancements have significant implications for improving human-computer interaction, creating realistic virtual characters, and designing assistive robotics, as well as enhancing medical procedures like craniomaxillofacial surgery planning.