REAL-TIME BODY POSE ESTIMATION SYSTEM AND METHOD IN UNCONSTRAINED VIDEO

In one or more implementations, body features of a subject can be tracked and a pose estimation produced using an unconstrained video sequence. The video sequence constitutes a physical record of the body features of the subject. A set of 2D coordinates corresponding to the body features of the subject can be received from a first neural network and 2D Keypoints are detected and transmitted to a second neural network. The second neural network can return corresponding depth estimation values, which can be processed to generate a set of 3D coordinates that correspond to the body features of the subject in camera space. Furthermore, one or more non-linear optimizations can be applied to fit a predetermined skeleton to the generate 3D Keypoints, and produce the pose estimation corresponding to the body features of the subject.