CrowdMM '12最新文献

A closer look at photographers' intentions: a test dataset 仔细观察摄影师的意图:一个测试数据集

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390811

M. Lux, M. Taschwer, Oge Marques

引用次数: 10

Crowdsourced user interface testing for multimedia applications 多媒体应用程序的众包用户界面测试

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390813

Raynor Vliegendhart, E. Dolstra, J. Pouwelse

引用次数: 12

Crowdsourcing micro-level multimedia annotations: the challenges of evaluation and interface 众包微级多媒体注释:评价与界面的挑战

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390816

Sunghyun Park, Gelareh Mohammadi, Ron Artstein, Louis-Philippe Morency

引用次数: 33

Tagging tagged images: on the impact of existing annotations on image tagging 标记标记的图像:关于现有注释对图像标记的影响

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390807

César Moltedo, H. Astudillo, Marcelo Mendoza

引用次数: 5

Ground truth generation in medical imaging: a crowdsourcing-based iterative approach 医学成像中的地面真相生成:基于众包的迭代方法

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390808

A. Foncubierta-Rodríguez, H. Müller

{"title":"Ground truth generation in medical imaging: a crowdsourcing-based iterative approach","authors":"A. Foncubierta-Rodríguez, H. Müller","doi":"10.1145/2390803.2390808","DOIUrl":"https://doi.org/10.1145/2390803.2390808","url":null,"abstract":"As in many other scientific domains where computer--based tools need to be evaluated, also medical imaging often requires the expensive generation of manual ground truth. For some specific tasks medical doctors can be required to guarantee high quality and valid results, whereas other tasks such as the image modality classification described in this text can in sufficiently high quality be performed with simple domain experts. Crowdsourcing has received much attention in many domains recently as volunteers perform so--called human intelligence tasks for often small amounts of money, allowing to reduce the cost of creating manually annotated data sets and ground truth in evaluation tasks. On the other hand there has often been a discussion on the quality when using unknown experts. Controlling task quality has remained one of the main challenges in crowdsourcing approaches as potentially the persons performing the tasks may not be interested in results quality but rather their payment.\u0000 On the other hand several crowdsourcing platforms such as Crowdflower that we used allow creating interfaces and sharing them with only a limited number of known persons. The text describes the interfaces developed and the quality obtained through manual annotation of several domain experts and one medical doctor. Particularly the feedback loop of semi--automatic tools is explained. The results of an initial crowdsourcing round classifying medical images into a set of image categories were manually controlled by domain experts and then used to train an automatic system that visually classified these images. The automatic classification results were then used to manually confirm or refuse the automatic classes, reducing the time for the initial tasks.\u0000 Crowdsourcing platforms allow creating a large variety of interfaces for judgements. Whether used among known experts or paying for unknown persons, they allow increasing the speed of ground truth creation and limit the amount of money to be paid.","PeriodicalId":429491,"journal":{"name":"CrowdMM '12","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124083219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 72

Enhancing online 3D products through crowdsourcing 通过众包提升在线3D产品

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390820

Thi Phuong Nghiem, A. Carlier, Géraldine Morin, V. Charvillat

引用次数: 1

Crowdsourcing user interactions within web video through pulse modeling 通过脉冲建模在网络视频中众包用户交互

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390812

M. Avlonitis, K. Chorianopoulos, David A. Shamma

引用次数: 1

Pushing the limits of mechanical turk: qualifying the crowd for video geo-location 突破土耳其机器人的极限:让人群具备视频地理定位的资格

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390815

L. Gottlieb, Jaeyoung Choi, P. Kelm, T. Sikora, G. Friedland

引用次数: 16

PodCastle and songle: crowdsourcing-based web services for spoken content retrieval and active music listening PodCastle和songle:基于众包的网络服务，用于口语内容检索和主动音乐收听

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390805

Masataka Goto, J. Ogata, Kazuyoshi Yoshii, Hiromasa Fujihara, Matthias Mauch, Tomoyasu Nakano

{"title":"PodCastle and songle: crowdsourcing-based web services for spoken content retrieval and active music listening","authors":"Masataka Goto, J. Ogata, Kazuyoshi Yoshii, Hiromasa Fujihara, Matthias Mauch, Tomoyasu Nakano","doi":"10.1145/2390803.2390805","DOIUrl":"https://doi.org/10.1145/2390803.2390805","url":null,"abstract":"In this keynote talk, we describe two crowdsourcing-based web services, PodCastle (http://en.podcastle.jp for the English version and http://podcastle.jp for the Japanese version) and Songle (http://songle.jp). PodCastle and Songle collect voluntary contributions by anonymous users in order to improve the experiences of users listening to speech and music content available on the web. These services use automatic speech-recognition and music-understanding technologies to provide content analysis results, such as full-text speech transcriptions and music scene descriptions, that let users enjoy content-based multimedia retrieval and active browsing of speech and music signals without relying on metadata.\u0000 When automatic content analysis is used, however, errors are inevitable. PodCastle and Songle therefore provide an efficient error correction interface that let users easily correct errors by selecting from a list of candidate alternatives. Through these corrections, users gain a real sense of contributing for their own benefit and that of others and can be further motivated to contribute by seeing corrections made by other users.\u0000 Our services promote the popularization and use of speech-recognition and music-understanding technologies by raising user awareness. Users can grasp the nature of those technologies just by seeing results obtained when the technologies applied to speech data and songs available on the web.","PeriodicalId":429491,"journal":{"name":"CrowdMM '12","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124416526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Tag suggestion on youtube by personalizing content-based auto-annotation 通过个性化基于内容的自动注释在youtube上标记建议

CrowdMM '12 Pub Date : 2012-10-29 DOI: 10.1145/2390803.2390819

Dominik Henter, Damian Borth, A. Ulges

{"title":"Tag suggestion on youtube by personalizing content-based auto-annotation","authors":"Dominik Henter, Damian Borth, A. Ulges","doi":"10.1145/2390803.2390819","DOIUrl":"https://doi.org/10.1145/2390803.2390819","url":null,"abstract":"We address the challenge of tag recommendation for web video clips on portals such as YouTube. In a quantitative study on 23,000 YouTube videos, we first evaluate different tag suggestion strategies employing user profiling (using tags from the user's upload history) as well as social signals (the channels a user subscribed to) and content analysis. Our results confirm earlier findings that --~at least when employing users' original tags as ground truth~-- a history-based approach outperforms other techniques. Second, we suggest a novel approach that integrates the strengths of history-based tag suggestion with a content matching crowd-sourced from a large repository of user generated videos. Our approach performs a visual similarity matching and merges neighbors found in a large-scale reference dataset of user-tagged content with others from the user's personal history. This way, signals gained by crowd-sourcing can help to disambiguate tag suggestions, for example in cases of heterogeneous user interest profiles or non-existing user history. Our quantitative experiments indicate that such a personalized tag transfer gives strong improvements over a standard content matching, and moderate ones over a content-free history-based ranking.","PeriodicalId":429491,"journal":{"name":"CrowdMM '12","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129684562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2