Crowd-Sourcing Design: Sketch Minimization using Crowds for Feedback

Engel, David (Massachusetts Institute of Technology) | Kottler, Verena (Max Planck Institute for Developmental Biology) | Malisi, Christoph (Max Planck Institute for Developmental Biology) | Roettig, Marc (University of Tuebingen) | Willing, Eva-Maria (Max Planck Institute for Plant-Breeding Research) | Schultheiss, Sebastian (Computonics.com)

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Design tasks are notoriously difficult, because success is defined by the perception of the target audience, whose feedback is usually not available during design stages. Commonly, design is performed by professionals who have specific domain knowledge (i.e., an intuitive understanding of the implicit requirements of the task) and do not need the feedback of the perception of the viewers during the process. In this paper, we present a novel design methodology for creating minimal sketches of objects that uses an iterative optimization scheme. We define minimality for a sketch via the minimal number of straight line segments required for correct recognition by 75% of naiive viewers. Crowd-sourcing techniques allow us to directly include the perception of the audience in the design process. By joining designers and crowds, we are able to create a human computation system that can efficiently optimize sketches without requiring high levels of domain knowledge (i.e., design skills) from any worker.

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