Multi-View Inpainting for Image-Based Scene Editing and Rendering

T. Thonat, Eli Shechtman, Sylvain Paris, G. Drettakis
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引用次数: 26

Abstract

We propose a method to remove objects such as people and cars from multi-view urban image datasets, enabling free-viewpoint IBR in the edited scenes. Our method combines information from multi-view 3D reconstruction with image inpainting techniques, by formulating the problem as an optimization of a global patch-based objective function. We use Image-Based Rendering (IBR) techniques to reproject information from neighboring views, and 3D multi-view stereo reconstruction to perform multiview coherent initialization for inpainting of pixels not filled by reprojection. Our algorithm performs multi-view consistent inpainting for color and 3D by blending reprojections with patch-based image inpainting. We run our algorithm on casually captured datasets, and Google StreetViewdata, removing objects cars, people and pillars, showing that our approach produces results of sufficient quality for free-viewpoint IBR on "cleaned up" scenes, as well as IBR scene editing, such as limited motion of real objects.
多视图绘画基于图像的场景编辑和渲染
我们提出了一种从多视点城市图像数据集中去除人物和汽车等物体的方法,从而在编辑后的场景中实现自由视点IBR。我们的方法结合了多视图三维重建和图像绘制技术的信息,通过将问题表述为基于全局补丁的目标函数的优化。我们使用基于图像的渲染(IBR)技术来重新投影来自相邻视图的信息,并使用3D多视图立体重建来执行多视图相干初始化,以重新绘制未被重新投影填充的像素。我们的算法通过混合重投影和基于补丁的图像绘制来执行彩色和3D的多视图一致性绘制。我们在随机捕获的数据集和Google StreetViewdata上运行我们的算法,删除对象汽车,人和柱子,表明我们的方法产生了足够质量的结果,用于“清理”场景的自由视点IBR,以及IBR场景编辑,例如真实物体的有限运动。
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