基于分割的三维视频视图合成

Maziar Loghman, Joohee Kim
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引用次数: 1

摘要

本文研究了分割在三维视频视图合成中的应用。视图合成是使用一组视图作为参考,生成场景的新视图的过程。最近,人们提出了几种使用深度图绘制虚拟视图的技术。然而,深度图的不准确性在基于深度的视图合成中会导致令人讨厌的视觉伪影。提出了一种基于多级阈值分割的高效深度图像绘制技术。该算法首先对所有图像进行深度分割,对不同对象的像素分别进行变形和混合;提出了一种基于多级阈值分割的模糊轮廓像素查找算法,简化了计算过程。提出了一种利用分割后的图像寻找相关联的背景边界像素点的图像分割方法。实验结果表明,对于多视点视频测试序列,该算法将合成视点的PSNR提高到0.68 dB,消除了恼人的视觉伪影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation-based view synthesis for three-dimensional video
This paper investigates the use of segmentation in view synthesis for three-dimensional video. View synthesis is the process of generating novel views of a scene, using a set of views as the reference. Recently, several techniques that use depth maps for rendering virtual views have been suggested. However, inaccuracy in depth maps causes annoying visual artifacts in depth-based view synthesis. This paper presents an efficient depth image-based rendering technique based on segmentation using multi-level thresholding. In the proposed algorithm, first all the images are segmented according to the depth and the pixels belonging to different objects are warped and blended independently. Based on multi-level thresholding, an algorithm for finding the ghost contour pixels is provided which simplifies the computations. A novel inpainting method for disocclusions has been introduced which uses the segmented images to find the associated background boundary pixels. The experimental results show that the proposed algorithm improves the PSNR of the synthesized views up to 0.68 dB for the multi-view video test sequences and eliminates the annoying visual artifacts.
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