{"title":"湘南会議 The future of multimedia analysis and mining","authors":"N. Boujemaa, Alexander Hauptmann, S. Satoh","doi":"10.2201/NIIPI.2014.11.1","DOIUrl":null,"url":null,"abstract":"Recent explosive growth of the amount of accessible multimedia information requires far more intelligent access to multimedia data. Multimedia analysis and mining play a key role to address this problem. For instance, multimedia analysis enables semantic access to multimedia information at any description level and for any applications or needs, even though the original multimedia data may not have any prior semantic annotation. Multimedia mining helps to provide highlevel semantic and structural information to expose key information within a large-scale multimedia database. However, the development of such technologies is often severely limited due to the famous “Semantic Gap” in multimedia content analysis. This is well-known as a supremely difficult issue that is very hard to overcome. On the other hand, researchers in this field now have access to far more computational resources thanks to recent developments in GPU use, multi-core technologies or the availability of cloud computing, as well as far more data resources thanks to the explosive growth of available multimedia data especially via Web. Several research projects have already begun to take advantage of these points independently. Based on the objective, we organized shonan meeting on “The Future of Multimedia Analysis and Mining,” from 3 to 6, November, 2012. In this meeting, we aim to discuss recent research trends and their impact on multimedia research. Then we consolidate key research challenges and explore promising new research directions, hopefully toward “Bridging the semantic gap.” Following the meeting, we organized the special issue on “The Future of Multimedia Analysis and Mining” in the Progress in Informatics. Important topics include the following:","PeriodicalId":91638,"journal":{"name":"... Proceedings of the ... IEEE International Conference on Progress in Informatics and Computing. IEEE International Conference on Progress in Informatics and Computing","volume":"9 1","pages":"41-44"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"... Proceedings of the ... IEEE International Conference on Progress in Informatics and Computing. IEEE International Conference on Progress in Informatics and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2201/NIIPI.2014.11.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

Recent explosive growth of the amount of accessible multimedia information requires far more intelligent access to multimedia data. Multimedia analysis and mining play a key role to address this problem. For instance, multimedia analysis enables semantic access to multimedia information at any description level and for any applications or needs, even though the original multimedia data may not have any prior semantic annotation. Multimedia mining helps to provide highlevel semantic and structural information to expose key information within a large-scale multimedia database. However, the development of such technologies is often severely limited due to the famous “Semantic Gap” in multimedia content analysis. This is well-known as a supremely difficult issue that is very hard to overcome. On the other hand, researchers in this field now have access to far more computational resources thanks to recent developments in GPU use, multi-core technologies or the availability of cloud computing, as well as far more data resources thanks to the explosive growth of available multimedia data especially via Web. Several research projects have already begun to take advantage of these points independently. Based on the objective, we organized shonan meeting on “The Future of Multimedia Analysis and Mining,” from 3 to 6, November, 2012. In this meeting, we aim to discuss recent research trends and their impact on multimedia research. Then we consolidate key research challenges and explore promising new research directions, hopefully toward “Bridging the semantic gap.” Following the meeting, we organized the special issue on “The Future of Multimedia Analysis and Mining” in the Progress in Informatics. Important topics include the following:
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多媒体的未来分析与挖掘
最近可访问多媒体信息量的爆炸式增长要求对多媒体数据进行更智能的访问。多媒体分析和挖掘是解决这一问题的关键。例如,多媒体分析支持在任何描述级别上、针对任何应用程序或需求对多媒体信息进行语义访问,即使原始多媒体数据可能没有任何先前的语义注释。多媒体挖掘有助于提供高级语义和结构信息,以公开大型多媒体数据库中的关键信息。然而,由于多媒体内容分析中著名的“语义鸿沟”,这些技术的发展往往受到严重限制。众所周知,这是一个非常困难的问题,很难克服。另一方面,由于GPU使用的最新发展,多核技术或云计算的可用性,这一领域的研究人员现在可以获得更多的计算资源,同时由于可用多媒体数据的爆炸性增长,特别是通过Web,可以获得更多的数据资源。几个研究项目已经开始独立地利用这些点。基于这一目标,我们于2012年11月3日至6日组织了关于“多媒体分析和挖掘的未来”的研讨会。在这次会议上,我们的目标是讨论最近的研究趋势及其对多媒体研究的影响。然后,我们整合关键的研究挑战,探索有前途的新研究方向,希望能够“弥合语义差距”。会议结束后,我们在《信息学进展》上组织了题为“多媒体分析和挖掘的未来”的特刊。重要议题包括:
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