Semantic 3D Human Pose Dictionary

Built a scalable pipeline to learn a unified 3D pose dictionary with semantic captions and compact embeddings. Normalized large-scale 3D skeleton data into a canonical representation and grouped poses using LSH-based clustering. Selected medoid poses as dictionary entries, enabling fast pose retrieval, action recognition, and motion understanding.