Using Human Computation in Dead-zone based 2D Pattern Matching
نویسندگان
چکیده
This paper examines the application of human computation (HC) to twodimensional 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.
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