A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
We propose a method to automatically detect 3D poses of closely interactive humans from sparse multi-view images at one time instance. It is a challenging problem due to the strong partial occlusion and truncation between humans and no tracking process to provide priori poses information. To solve this problem, we first obtain 2D joints in every image using OpenPose and human semantic segmentation results from Mask R-CNN. With the 3D joints triangulated from multi-view 2D joints, a two-stagedoi:10.3390/s19122831 pmid:31242651 pmcid:PMC6631029 fatcat:msi6lhob3bfhtc74qjou4fqh6e