Conf42: JavaScript 2022

Algorithmically Generated Visual Designs

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This past summer, I worked with two undergraduate students (Alyssa Zhang and Maya Newman-Toker) and one software engineer (John Mancini) on a research project that investigates computer generated artwork. During this investigation, we designed and implemented nine algorithms that generate visual designs. Our algorithms, coded in JavaScript, are built from procedural processes that draw lines and basic shapes onto a digital canvas. These procedural processes were inspired by mathematical concepts, natural phenomena, and artistic trends, but contain many parameters to allow for image variation. We used our algorithms to build a dataset of over 1,000 algorithmically generated artworks, which we recruited reviewers to compare and rate. We plan to analyze the reviewers’ ratings to find associations between different parameterizations of our algorithms and the response of reviewers to the resulting images.

Check out the GitHub repo


Michael Wehar

Visiting Assistant Professor @ Swarthmore College

Michael Wehar's LinkedIn account

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