Diamonds From the Rough: Improving Drawing, Painting, and Singing via Crowdsourcing
Yotam Gingold, Etienne Vouga, Eitan Grinspun, Haym Hirsh
In Proceedings of the AAAI Workshop on Human Computation (HCOMP), Toronto, Canada, July 2012.

Paper: PDF (2M)
Poster: PDF (6M)
Data (inputs and composites): drawing (1M, zipped) | painting (1M, zipped) | singing (35M, zipped)

The median of many paintings of a pear photograph.

Abstract

It is well established that in certain domains, noisy inputs can be reliably combined to obtain a better answer than any individual. It is now possible to consider the crowdsourcing of physical actions, commonly used for creative expressions such as drawing, shading, and singing. We provide algorithms for converting low-quality input obtained from the physical actions of a crowd into high-quality output. The inputs take the form of line drawings, shaded images, and songs. We investigate single-individual crowds (multiple inputs from a single human) and multiple-individual crowds.

BibTeX

@inproceedings{Gingold:2012:DFR,
 author    = {Yotam Gingold and Etienne Vouga and Eitan Grinspun and Haym Hirsh},
 title     = {Diamonds From the Rough: {I}mproving Drawing, Painting, and Singing via Crowdsourcing},
 booktitle = {Proceedings of the AAAI Workshop on Human Computation (HCOMP)},
 year      = {2012},
 location  = {Toronto, Canada}
}