Temporal Skeleton

Temporal skeleton analysis focuses on understanding human actions and activities by analyzing the movement of skeletal joints over time, primarily using 3D skeletal data extracted from video. Current research emphasizes developing efficient and robust algorithms, often employing graph convolutional networks, transformers, and attention mechanisms, to improve accuracy and speed in tasks like action recognition, anomaly detection, and sign language recognition. These advancements have significant implications for various applications, including healthcare (e.g., seizure detection), security (e.g., anomaly detection), and assistive technologies (e.g., sign language translation), by enabling more accurate and efficient analysis of human motion.