Abstract
View synthesis is a crucial technique for free viewpoint video and multi-view video coding because of its capability to render an unlimited number of virtual viewpoints from adjacent captured texture images and corresponding depth maps. The accuracy of depth maps is very important to the rendering quality, since depth image–based rendering (DIBR) is the most widely used technology among synthesis algorithms. There are some issues due to the fact that stereo depth estimation is error-prone. In addition, filling occlusions is another challenge in producing desirable synthesized images. In this paper, we propose a reliability-based view synthesis framework. A depth refinement method is used to check the reliability of depth values and refine some of the unreliable pixels, and an adaptive background modeling algorithm is utilized to construct a background image aiming to fill the remaining empty regions after a proposed weighted blending process. Finally, the proposed approach is implemented and tested on test video sequences, and experimental results indicate objective and subjective improvements compared to previous view synthesis methods.
Highlights
In the past few decades, three-dimensional video has been widely adopted in various applications.Free viewpoint video (FVV) is a novel display format that has evolved from 3D video that enables viewers to watch a scene from any position [1]
depth image–based rendering (DIBR) utilizes one or more reference texture images and their associated depth images to synthesize virtual view images, wherein every pixel in the original reference image plane is projected to the 3D world coordinate system according to its associated depth value; thereafter the 3D world coordinates are projected onto the image plane in the virtual viewpoint [4]
Was adaptive background modeling method evolving from Gaussian mixture model (GMM) to generate utilized to construct a stableis background image to fill large to empty regions
Summary
In the past few decades, three-dimensional video has been widely adopted in various applications. The projected float results lead to rounding errors, which further cause pinholes, cracks, and blurs In addition to these artifacts, a critical problem arises during the generation of virtual images, since the regions covered by foreground objects in the reference views may be disoccluded in the virtual viewpoints, and these areas will appear as large holes in the virtual view, referred to as disocclusions. We propose a novel synthesis framework using two reference viewpoints This method first determines whether the pixel-wise depth map is reliable or unreliable, refines some of those unreliable depth values. The proposed adaptive median filter and depth map processing method (DMPM) show satisfactory performance on reduction of noise and other unwanted effects while the texture images remain sharp and clear.
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