Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1833349.1778820 | ACM Transactions on Graphics |
Keywords | Field | DocType |
image rearrangement,novel boundary band method,deformation propagation,repeated instance,scene element,missing part,novel framework,repeated element,high level task,illumination variation,detection process,shape-aware manipulation,image editing,edit propagation | Computer vision,Edit propagation,Computer graphics (images),Computer science,Image editing,Artificial intelligence | Journal |
Volume | Issue | Citations |
29 | 4 | 66 |
PageRank | References | Authors |
1.61 | 39 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ming-Ming Cheng | 1 | 1914 | 82.32 |
| Fang-Lue Zhang | 2 | 269 | 15.60 |
| Niloy J. Mitra | 3 | 3813 | 176.15 |
| Xiaolei Huang | 4 | 1084 | 63.94 |
| Shi-Min Hu | 5 | 3466 | 188.22 |