AAAI Publications, First AAAI Conference on Human Computation and Crowdsourcing

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Real-Time Drawing Assistance through Crowdsourcing
Alex Limpaecher, Nicolas Feltman, Adrien Treuille, Michael Cohen

Last modified: 2013-11-03

Abstract


We propose a new method for the large-scale collection and analysis of drawings by using a mobile game specifically designed to collect such data. Analyzing this crowdsourced drawing database, we build a spatially varying model of artistic consensus at the stroke level. We then present a surprisingly simple stroke- correction method which uses our artistic consensus model to improve strokes in real-time. Importantly, our auto-corrections run interactively and appear nearly in- visible to the user while seamlessly preserving artistic intent. Closing the loop, the game itself serves as a plat- form for large-scale evaluation of the effectiveness of our stroke correction algorithm.

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