A survey of recent interactive image segmentation methods

• 来源期刊: 计算可视媒体（英文版）
• 年，卷（期）: 2020,（4）
• 所属期刊栏目: REVIEW ARTICLE
• 页码范围: 355-384
• 页数: 30页
• 语种: 英文

摘要

Image segmentation is one of the most basic tasks in computer vision and remains an initial step of many applications. In this paper, we focus on interactive image segmentation (IIS), often referred to as foreground–background separation or object extraction, guided by user interaction. We provide an overview of the ⅡS literature by covering more than 150 publications, especially recent works that have not been surveyed before. Moreover, we try to give a comprehensive classification of them according to different viewpoints and present a general and concise comparison of the most recent published works. Furthermore, we survey widely used datasets, evaluation metrics, and available resources in the field of ⅡS.