Spatio Temporal Trajectory

Spatio-temporal trajectory analysis focuses on understanding movement patterns and travel behaviors from sequential location data. Current research emphasizes developing robust and versatile models, including those leveraging large language models and self-supervised learning techniques, to extract meaningful information from trajectories, often represented as probability distributions or vectorized features. These advancements enable improved performance in diverse applications such as activity recognition, POI recommendation, and geospatial computer vision, ultimately contributing to a deeper understanding of human and robotic mobility.