Cross-media retrieval: state-of-the-art and open issues

Cross-media retrieval: state-of-the-art and open issues
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跨媒体检索:最先进的和开放的问题

DOI:
10.1504/ijmis.2010.035970
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发表时间:
2010-10
期刊:
International Journal of Multimedia Intelligence and Security
影响因子:
--
通讯作者:
Hanqing Lu
Hanqing Lu
中科院分区:
其他
文献类型:
--
作者:
Jing Liu;Changsheng Xu;Hanqing Lu

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跨媒体检索能够为查询提供语义相似但媒体不同的检索结果。由于跨媒体检索是对当前流行的基于文本/内容的检索的补充,基于文本/内容的检索为查询提供具有相同媒体的检索结果,因此成为一个新兴的研究课题。本文对跨媒体检索的最新进展和面临的研究挑战进行了综述。这种检索模式是由网络上广泛可用的大量多媒体资源、从语义上理解各种多媒体对象的创新方法以及用于在不同特征空间之间进行交互映射的新颖机器学习技术驱动的。在这些方面,我们回顾了最先进的方法和取得的进展,跨媒体检索。根据目前跨媒体检索所使用的技术和现实应用的需求,确定了有待解决的研究问题和未来的研究机会。
Cross-media retrieval is able to provide retrieval results with similar semantics but different media to the query. Since cross-media retrieval complements currently popular text/content-based retrieval which provides retrieval results with the same media to the query, it becomes an emerging research topic. In this paper, we give an overview of recent advances and research challenges in cross-media retrieval. Such retrieval paradigm has been driven by the wide availability of large multimedia resources on the web, innovative approaches to semantically understanding various multimedia objects, and novel machine learning techniques for the interactive mappings among heterogeneous feature spaces. Emphasising on these respects, we review the state-of-the-art approaches and achieved progresses in cross-media retrieval. According to the current technologies used in cross-media retrieval and the demand from real-world applications, open research issues and future research opportunities are identified.
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