RepSnapping: Efficient Image Cutout for Repeated Scene Elements

Abstract

Repeated scene elements are copious and ubiquitous in natural images. Cutout of those repeated elements usually involves tedious and laborious user interaction by previous image segmentation methods. In this paper, we present RepSnapping, a novel method oriented to cutout of repeated scene elements with much less user interaction. By exploring inherent similarity between repeated elements, a new optimization model is introduced to thread correlated elements in the segmentation procedure. The model proposed here enables efficient solution using maxflow/ min cut on an extended graph. Experiments indicate that RepSnapping facilitates cutout of repeated elements better than the state-of-the-art interactive image segmentation and repetition detection methods.