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Repfinder: Finding approximately repeated scene elements for image editing

机译:Repfinder:查找近似重复的场景元素以进行图像编辑

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摘要

Repeated elements are ubiquitous and abundant in both manmade and natural scenes. Editing such images while preserving the repetitions and their relations is nontrivial due to overlap, missing parts, deformation across instances, illumination variation, etc. Manually enforcing such relations is laborious and error-prone. We propose a novel framework where user scribbles are used to guide detection and extraction of such repeated elements. Our detection process, which is based on a novel boundary band method, robustly extracts the repetitions along with their deformations. The algorithm only considers the shape of the elements, and ignores similarity based on color, texture, etc. We then use topological sorting to establish a partial depth ordering of overlapping repeated instances. Missing parts on occluded instances are completed using information from other instances. The extracted repeated instances can then be seamlessly edited and manipulated for a variety of high level tasks that are otherwise difficult to perform. We demonstrate the versatility of our framework on a large set of inputs of varying complexity, showing applications to image rearrangement, edit transfer, deformation propagation, and instance replacement. © 2010 ACM.
机译:在人造和自然场景中,重复元素无处不在且丰富。由于重叠,部分丢失,实例变形,光照变化等原因,在保留重复及其关系的同时编辑此类图像非常重要。手动执行此类关系既费力又容易出错。我们提出了一种新颖的框架,其中用户涂鸦可用于指导检测和提取此类重复元素。我们的检测过程基于一种新颖的边界带方法,能够可靠地提取出重复及其变形。该算法仅考虑元素的形状,而忽略基于颜色,纹理等的相似性。然后,我们使用拓扑排序来建立重叠重复实例的局部深度排序。使用其他实例中的信息来完成被阻塞实例上的缺失部分。然后可以针对各种原本难以执行的高级任务,对提取的重复实例进行无缝编辑和操作。我们在复杂性各异的大量输入中展示了我们框架的多功能性,展示了图像重排,编辑传递,变形传播和实例替换的应用。 ©2010 ACM。

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