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Bayesian based view synthesis for multi-planar structures

机译:基于贝叶斯的多平面结构视图综合

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With the rapid development of mobile applications in recent years, there is a strong desire on light weight algorithm for view synthesis using uncalibrated images and limited geometry information. To address this challenge, we propose a Bayesian based view synthesis framework to support the rendering of complex scene with multiple planar structures. In this framework, we integrate image segmentation, reference plane selection and hole filling with a Bayesian formulation to perform view synthesis without using 3D geometry information. More specifically, we partition every reference image into multiple planes, estimate geometric and photometric parameters for each plane, synthesize the novel view by Bayesian modeling using selected reference planes, and refine the rendered image by a hole filling scheme. The entire view synthesis process is executed in an iterative manner to pursue high quality visual results. The experimental results show that the proposed method is able to achieve desired performance with less distortion and higher resolution.
机译:近年来,随着移动应用程序的快速发展,人们强烈希望使用轻量级算法来使用未校准的图像和有限的几何信息进行视图合成。为了解决这一挑战,我们提出了一种基于贝叶斯的视图综合框架,以支持具有多个平面结构的复杂场景的渲染。在此框架中,我们将图像分割,参考平面选择和孔填充与贝叶斯公式集成在一起,以在不使用3D几何信息的情况下执行视图合成。更具体地说,我们将每个参考图像划分为多个平面,估计每个平面的几何和光度参数,使用选定的参考平面通过贝叶斯建模合成新颖的视图,并通过孔填充方案细化渲染的图像。整个视图合成过程以迭代方式执行,以追求高质量的视觉效果。实验结果表明,所提出的方法能够以较小的失真和较高的分辨率实现所需的性能。

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