论文标题
用于提取图像及其周围上下文信息的网页细分
Webpage Segmentation for Extracting Images and Their Surrounding Contextual Information
论文作者
论文摘要
Web图像与有价值的上下文信息有关。尽管长期以来已开采此信息，以用于各种用途，例如图像注释，图像的聚类，图像语义内容的推理等，但仍未充分关注来解决挖掘此上下文信息的问题。在本文中，我们提出了一种网页分割算法，该算法针对Web图像提取及其上下文信息，基于它们在网页上出现的特征。我们进行了一项用户研究，以获取人体标记的数据集，以验证我们方法的有效性，实验表明，与现有的分割算法相比，我们的方法可以取得更好的结果。
Web images come in hand with valuable contextual information. Although this information has long been mined for various uses such as image annotation, clustering of images, inference of image semantic content, etc., insufficient attention has been given to address issues in mining this contextual information. In this paper, we propose a webpage segmentation algorithm targeting the extraction of web images and their contextual information based on their characteristics as they appear on webpages. We conducted a user study to obtain a human-labeled dataset to validate the effectiveness of our method and experiments demonstrated that our method can achieve better results compared to an existing segmentation algorithm.
