A New Free Viewpoint Video Dataset and DIBR Benchmark

Shuai Guo

Abstract: Free viewpoint video (FVV) has drawn great attention in recent years, which provides viewers with strong interactive and immersive experience. Despite the developments made, further progress of FVV research is limited by existing datasets that mostly have too few number of camera views, or static scenes. To overcome the limitations, in this paper, we present a new dynamic RGB-D video dataset with up to 12 views. Our dataset consists of 13 groups of dynamic video sequences that are taken at the same scene, and a group of video sequences of the empty scene. Each group has 12 HD video sequences taken by synchronized cameras and 12 correspondingly estimated depth video sequences. Moreover, we also introduce a FVV synthesis benchmark on the basis of depth image based rendering (DIBR) to help researchers validate their data-driven methods.We hope our work will inspire more FVV synthesis methods with enhanced robustness, improved performance and deeper understanding.