Effect of a confidence-based weighted 3D point reconstruction for markerless motion capture with a reduced number of cameras

Markerless motion capture has been made available by the development of pose estimation algorithms that provide both an estimate of the location of body keypoints in two-dimensional images and its associated confidence. It seems relevant to use this additional information for three-dimensional (3D) point reconstruction. Yet, it has been little described, nor has its influence on 3D point reconstruction. Eight participants performed a manual material handling task, which was recorded by 10 video cameras. Each video was processed using OpenPose. Different 3D point reconstruction methods were compared: direct linear transform (DLT) and weighted DLT (wDLT), with 10 cameras and with a subset of 4 cameras. For each keypoint, confidence and position deviation from the 3D reconstructed point with 10 cameras projected in the image reference frame were assessed. Results suggest that using confidence information reduces both average and maximum 3D distance between 3D points reconstructed with 4 and 10 cameras.