{"title":"第四届多媒体众包国际研讨会论文集","authors":"J. Redi, S. Rudinac","doi":"10.1145/2810188","DOIUrl":null,"url":null,"abstract":"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. \n \nSince 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. \n \nThe 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. \n \nCrowdMM15 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.","PeriodicalId":284531,"journal":{"name":"Proceedings of the Fourth International Workshop on Crowdsourcing for Multimedia","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Proceedings of the Fourth International Workshop on Crowdsourcing for Multimedia\",\"authors\":\"J. Redi, S. Rudinac\",\"doi\":\"10.1145/2810188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. \\n \\nSince 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. \\n \\nThe 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. \\n \\nCrowdMM15 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. 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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.