Pose Estimation Tutorial: Creating Pose Skeletons from Scratch

Human pose estimation is a crucial component of computer vision, enabling machines to understand spatial relationships and dynamics from visual data by detecting anatomical features within images and videos. This technique leverages advanced deep learning models, such as CNNs and transformer-based architectures, to address challenges like occlusion and motion blur. Applications of pose estimation span robotics, sports analytics, healthcare, and augmented reality, making it a key area of AI research. The tutorial on pose estimation with FiftyOne and CVAT guides users through creating and annotating pose skeletons using keypoint-based annotations, facilitating efficient dataset preparation and annotation workflows. FiftyOne's integration with CVAT allows for streamlined skeleton annotation, making the process accessible to both novices and experienced practitioners, thereby enhancing computer vision and machine learning projects.