OpenPose is an open-source software library developed by the Carnegie Mellon Perceptual Computing Lab. It enables real-time multi-person detection of body, face, and hand keypoints in images and videos. By using deep learning techniques, OpenPose can accurately track human poses and movements, making it useful for various applications in fields like sports analysis, animation, and virtual reality. The technology works by analyzing visual data to identify keypoints, such as joints and facial features, and then connecting them to form a skeleton-like representation of the human body. This allows for detailed motion capture and analysis, enhancing the understanding of human behavior and interaction.