Real-Time Drawing Assistance through Crowdsourcing

2013-11-10

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 1

Volume

Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing

Demonstrations

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.

10.1609/hcomp.v1i1.13058