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首页> 外文会议>Proceedings of the Twenty-Third international joint conference on artificial intelligence >Automatic Name-Face Alignment to Enable Cross-Media News Retrieval
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Automatic Name-Face Alignment to Enable Cross-Media News Retrieval

机译：自动名称对位对齐以启用跨媒体新闻检索

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摘要

A new algorithm is developed in this paper to support automatic name-face alignment for achieving more accurate cross-media news retrieval.We focus on extracting valuable information from large amounts of news images and their captions,where multi-level image-caption pairs are constructed for characterizing both significant names with higher salience and their cohesion with human faces extracted from news images.To remedy the issue of lacking enough related information for rare name,Web mining is introduced to acquire the extra multimodal information.We also emphasize on an optimization mechanism by our Improved Self-Adaptive Simulated Annealing Genetic Algorithm to verify the feasibility of alignment combinations.Our experiments have obtained very positive results.
机译：本文开发了一种新的算法来支持自动的人脸名称对齐，以实现更准确的跨媒体新闻检索。我们专注于从大量新闻图像及其标题中提取有价值的信息，其中多级图像标题对是构造用于表征具有较高显着性的重要名称以及它们与从新闻图像中提取的人脸的衔接。为解决稀有名称缺少足够的相关信息的问题，引入了Web挖掘以获取额外的多模式信息。我们还强调了优化通过改进的自适应模拟退火遗传算法验证比对组合的可行性。我们的实验取得了非常积极的成果。

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  • 来源
  • 会议地点 Beijing(CN)
  • 作者

    Yuejie Zhang; Wei Wu; Yang Li; Cheng Jin; Xiangyang Xue; Jianping Fan;

  • 作者单位

    School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,Shanghai,China;

    School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,Shanghai,China;

    School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,Shanghai,China;

    School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,Shanghai,China;

    School of Computer Science,Shanghai Key Laboratory of Intelligent Information Processing,Fudan University,Shanghai,China;

    Department of Computer Science,The University of North Carolina at Charlotte,USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;
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