A Framework for crowdsourced multimedia processing and querying

Alessandro Bozzon, Ilio Catallo, Eleonora Ciceri, Piero Fraternali, Davide Martinenghi, Marco Tagliasacchi

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)


This paper introduces a conceptual and architectural frame- work for addressing the design, execution and verification of tasks by a crowd of performers. The proposed framework is substantiated by an ongoing application to a problem of trademark logo detection in video collections. Preliminary results show that the contribution of crowds can improve the recall of state-of-the-art traditional algorithms, with no loss in terms of precision. However, task-to-executor matching, as expected, has an important influence on the task performance.

Original languageEnglish
Pages (from-to)3-8
Number of pages6
JournalCEUR Workshop Proceedings
Publication statusPublished - 2012
Externally publishedYes


  • Crowdsourcing
  • Human Computation
  • Multimedia


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