Interactive image segmentation algorithms rely on the user to provide annotations as the guidance. When the task of interactive segmentation is performed on a small touchscreen device, the requirement of providing precise annotations could be cumbersome to the user. We design a new interaction mechanism that actively queries seeds for guiding the user to label. Our method enforces sparsity and diversity criteria on the selection of query seeds, and at each round of interaction, the user is only presented with a small number of informative query seeds that are far apart from each other. Therefore, the user merely has to swipe through on the ROI-relevant query seeds for checking which ones of the query seeds are inside the region of interest (ROI). This kind of interaction should be easy since those gestures are commonly used on a touchscreen. As a result, we are able to derive a user-friendly interaction mechanism for annotation on small touchscreen devices. The performance of our algorithm is evaluated on six publicly available datasets. The evaluation results show that our algorithm achieves high segmentation accuracy, with short computational time and less user feedback.

中文翻译：

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SwipeCut：通过种子分组进行交互式分割

交互式图像分割算法依赖于用户提供注释作为指导。当在小型触摸屏设备上执行交互式分割任务时，提供精确注释的要求可能会给用户带来麻烦。我们设计了一种新的交互机制，主动查询种子以引导用户进行标记。我们的方法在选择查询种子时强制执行稀疏性和多样性标准，并且在每一轮交互中，用户只会看到少量彼此相距很远的信息查询种子。因此，用户只需在与 ROI 相关的查询种子上滑动以检查哪些查询种子在感兴趣区域 (ROI) 内。这种交互应该很容易，因为这些手势通常用于触摸屏。因此，我们能够为小型触摸屏设备上的注释推导出一种用户友好的交互机制。我们算法的性能在六个公开可用的数据集上进行评估。评估结果表明，我们的算法实现了高分割精度，计算时间短，用户反馈少。