Using human computation in dead-zone based 2D pattern matching

L.G.W.A. Cleophas, B.W. Watson, K. Awid

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    This paper examines the application of human computation (HC) to two-dimensional image pattern matching. The two main goals of our algorithm are to use turks as the processing units to perform an efficient pattern match attempt on a subsection of an image, and to divide the work using a version of dead-zone based pattern matching. In this approach, human computation presents an alternative to machine learning by outsourcing computationally difficult work to humans, while the dead-zone search offers an efficient search paradigm open to parallelization—making the combination a powerful approach for searching for patterns in two-dimensional images.
    Original languageEnglish
    Title of host publicationProceedings of the Prague Stringology Conference 2016, August 29-31, 2016, Prague, Czech Republic
    Place of Publications.l.
    Number of pages11
    ISBN (Print)978-80-01-05996-8
    Publication statusPublished - 2016
    EventPrague Stringology Conference 2016 - Prague, Czech Republic
    Duration: 29 Aug 201631 Aug 2016


    ConferencePrague Stringology Conference 2016
    Country/TerritoryCzech Republic


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