Real-time Pose Estimation using Tree Structures Built from Skeletonised Volume Sequences

Pose estimation in the context of human motion analysis is the process of approximating the body configuration in each frame of a motion sequence. We propose a novel pose estimation method based on constructing tree structures from skeletonised visual hulls reconstructed from multi-view video. The pose is estimated independently in each frame, so the method can recover from errors in previous frames, which overcomes the problems of tracking. Publically available datasets were used to evaluate the method. On real data the method performs at a framerate of 15–64 fps depending on the resolution of the volume. Using synthetic data the positions of the extremities were determined with a mean error of 47–53 mm depending on the resolution.