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Social image tagging using graph-based reinforcement on multi-type interrelated objects

机译：在多类型相关对象上使用基于图的增强功能进行社会图像标记

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摘要

Social image tagging is becoming increasingly popular with the development of social website, where images are annotated with arbitrary keywords called tags. Most of present image tagging approaches are mainly based on the visual similarity or mapping between visual feature and tags. However, in the social media environment, images are always associated with multi-type of object information (i.e., visual content, tags, and user contact information) which makes this task more challenging. In this paper, we propose to fuse multi-type of information to tag social image. Specifically, we model social image tagging as a "ranking and reinforcement" problem, and a novel graph-based reinforcement algorithm for interrelated multi-type objects is proposed. When a user issue a tagging request for a query image, a candidate tag set is derived and a set of friends of the query user is selected. Then a graph which contains three types of objects (i.e., visual features of the query image, candidate tags, and friend users) is constructed, and each type of objects are initially ranked based on their weight and intra-relation. Finally, candidate tags are re-ranked by our graph-based reinforcement algorithm which takes into consideration both inter-relation with visual features and friend users, and the top ranked tags are saved. Experiments on real-life dataset demonstrate that our algorithm significantly outperforms state-of-the-art algorithms.
机译：随着社交网站的发展，社交图像标记变得越来越流行，在社交网站中，图像使用称为标签的任意关键字进行注释。当前大多数图像标记方法主要基于视觉相似性或视觉特征与标签之间的映射。然而，在社交媒体环境中，图像总是与多种类型的对象信息（即，视觉内容，标签和用户联系信息）相关联，这使得该任务更具挑战性。在本文中，我们建议融合多种类型的信息以标记社会形象。具体来说，我们将社会图像标记建模为“排序和增强”问题，并提出了一种基于图的相互关联的多类型对象增强算法。当用户发出对查询图像的标记请求时，将得出候选标记集，并选择查询用户的一组朋友。然后，构建包含三种类型的对象（即查询图像的视觉特征，候选标签和朋友用户）的图形，并根据它们的权重和内部关系对每种类型的对象进行初始排名。最后，候选标记通过基于图形的增强算法重新排序，该算法考虑了与视觉特征和好友用户的相互关系，并保存了排名最高的标记。在真实数据集上进行的实验表明，我们的算法明显优于最新算法。

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  • 来源
    《Signal processing》 |2013年第8期|2178-2189|共12页
  • 作者

    Xiaoming Zhang; Xiaojian Zhao; Zhoujun Li; Jiali Xia; Ramesh Jain; Wenhan Chao;

  • 作者单位

    State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;

    State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;

    State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;

    School of Software, Jiangxi University of Finance & Economics, Nanchang, China;

    University of California. Irvine, CA, USA;

    State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Social image tagging; Image retrieval; Reinforcement; Tag ranking; Personal tagging;

    机译：社交图片标记;图像检索;加强;标签排名;个人标签;

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