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.
|Number of pages||6|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2012|
- Human Computation