Real-Time Free Viewpoint Video Synthesis System Based on DIBR and a Depth Estimation Network
Shuai Guo, Jingchuan Hu, Kai Zhou, Jionghao Wang, Li Song, Rong Xie, Wenjun Zhang
Abstract
Depth image-based rendering (DIBR) view synthesis is the most widely employed method in real-time FVV research. Despite recent progress, most DIBR-based FVV synthesis approaches are not sufficiently simple and effective in filling holes and artifacts. Additionally, they use RGB-D cameras, which are difficult to widely adopt or take considerable time to estimate high-quality depth images. This paper introduces a real-time FVV synthesis system based on DIBR and a depth estimation network. This system includes a 12-view synchronous camera system, a new multistage depth estimation network, a new GPU-accelerated DIBR algorithm, and a virtual view parameter generation method. This system provides the first real-time FVV solution for background-fixed fields based on DIBR and a depth estimation network. It can infer depth images for all camera views and synthesize any virtual view along the horizontal circular arc of the camera rig in real time. To our knowledge, we are the first to introduce background models and foreground masks and a refined multistage structure to address real-time high-quality depth estimation and DIBR FVV synthesis. We also build a high-quality multiview RGB-D synchronous dataset that has promising DIBR FVV synthesis performance to train and evaluate our system. The experimental results demonstrate the real-time and better performance of the proposed system.