Spatio-Temporal Upsampling for Free Viewpoint Video Point Clouds
Published in Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2019, 1969
This paper presents an approach to upsampling point cloud sequences captured through a wide baseline camera setup in a spatio-temporally consistent manner. The system uses edge-aware scene flow to understand the movement of 3D points across a free-viewpoint video scene to impose temporal consistency. In addition to geometric upsampling, a Hausdorff distance quality metric is used to filter noise and further improve the density of each point cloud. Results show that the system produces temporally consistent point clouds, not only reducing errors and noise but also recovering details that were lost in frame-by-frame dense point cloud reconstruction. The system has been successfully tested in sequences that have been captured via both static or handheld cameras.
Recommended citation: Moynihan, Matthew, Rafael Pagés, and Aljosa Smolic. "Spatio-temporal Upsampling for Free Viewpoint Video Point Clouds." VISIGRAPP (5: VISAPP). 2019. https://v-sense.scss.tcd.ie/wp-content/uploads/2020/05/mm2020Cloud_compressed.pdf