Abstract Image and video cosegmentation is a newly emerging and rapidly progressing area, which aims at delineating common objects at pixel-level from a group of images or a set of videos. Plenty of related works have been published and implemented in varied applications, but there lacks a systematic survey on both image and video cosegmentation. This paper provides a comprehensive overview including the existing methods, applications, and challenges. Specifically, different cosegmentation problem settings are described, the formulation details of the methods are summarized and their potential applications are listed. Moreover, the benchmark datasets and standard evaluation metrics are also given; and the future directions and unsolved challenges are discussed.

中文翻译：

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图像和视频协同分割调查：方法、挑战和分析

摘要 图像和视频协同分割是一个新兴且发展迅速的领域，其目的是从一组图像或一组视频中在像素级描绘常见对象。已经发表了大量相关工作并在各种应用中实现，但缺乏对图像和视频协同分割的系统调查。本文提供了一个全面的概述，包括现有的方法、应用和挑战。具体来说，描述了不同的二次分割问题设置，总结了方法的制定细节并列出了它们的潜在应用。此外，还给出了基准数据集和标准评估指标；并讨论了未来的方向和未解决的挑战。