第四届多媒体众包国际研讨会论文集

J. Redi, S. Rudinac
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引用次数: 1

摘要

众包有潜力解决多媒体研究中的关键挑战。多媒体评价、注释、检索和创建可以通过大量人群的贡献和利用人工计算以较低的时间和金钱成本获得。事实上,这一潜力的应用领域尚未被发现。然而,如何谨慎地利用它的挑战已经出现。人群作为一个用户(工人)社区,是一个复杂的动态系统,对其活动的形式变化和参数化高度敏感。有关动机、可靠性和参与的问题越来越多地被记录下来,需要加以解决。自2012年以来,ACM多媒体众包国际研讨会(CrowdMM)对有效部署众包以促进多媒体研究的新见解表示欢迎。今年是CrowdMM15的第四个年头,它专注于解决仍阻碍多媒体研究界广泛采用众包模式的关键挑战:远程监控用户行为、有效的测试设计、控制结果中的噪音和质量、设计不滋生作弊的激励结构,以及让用户(人群!)保持在循环中以促进多媒体应用的有效方法。论文征集吸引了大量国际投稿,其中两篇是短文。其中三份作为口头报告,四份作为海报。所有论文均获得至少3次双盲评审,平均3.5次评审。CrowdMM15还邀请了哥伦比亚大学的张世富教授,就众包在视频事件检测、情感分析和用户意图建模方面的应用进行主题演讲。此外,今年是CrowdMM第二年提出Crowdkeynote:一个众包主题演讲,在这个演讲中,CrowdMM社区的所有成员都发表了他们对未来和众包仍然面临的挑战的看法。Crowdkeynote的幻灯片可以在https://goo.gl/Xlur2E上找到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proceedings of the Fourth International Workshop on Crowdsourcing for Multimedia
Crowdsourcing has the potential to address key challenges in multimedia research. Multimedia evaluation, annotation, retrieval and creation can be obtained at a low time and monetary cost from the contribution of large crowds and by leveraging human computation. In fact, the applicative frontiers of this potential are yet to be discovered. And yet, challenges already arise as to how to cautiously exploit it. The crowd, as a users' (workers) community, is a complex and dynamic system highly sensitive to changes in the form and the parameterization of their activities. Issues concerning motivation, reliability, and engagement are being more and more often documented, and need to be addressed. Since 2012, the International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM) has welcomed new insights on the effective deployment of crowdsourcing towards boosting Multimedia research. On its fourth year, CrowdMM15 focuses on contributions addressing the key challenges that still hinder widespread adoption of crowdsourcing paradigms in the multimedia research community: remote monitoring of the user behavior, effective test design, controlling noise and quality in the results, designing incentive structures that do not breed cheating, and effective ways of keeping the user (the crowd!) in the loop to boost multimedia applications. The call for papers attracted a good number of international submissions, two of which short papers. Of these, three were accepted as oral presentations and four as posters. All papers received at least three double blind reviews, and 3.5 reviews on average. CrowdMM15 also proudly features the keynote talk of Prof. Shih-Fu Chang (Columbia University), addressing Crowdsourcing in video event detection, sentiment analysis and user intent modelling. Furthermore, for the second year this year CrowdMM proposes the Crowdkeynote: a crowd-sourced keynote, during which all members of the CrowdMM community give their view on the future and the Challenges that Crowdsourcing has still ahead. The slides of the Crowdkeynote can be found at https://goo.gl/Xlur2E.
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