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 between instances, illumination variation, etc. Manually enforcing such relations is laborious and error prone. We propose a novel framework where simple user input in the form of scribbles are used to guide detection and extraction of such repeated elements. Our detection process is based on a novel boundary band method, and robustly extracts the repetitions along with their mutual depth relations. 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 ou...
Ming-Ming Cheng, Fang-Lue Zhang, Niloy J. Mitra, X