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VisiFit: Structuring Iterative Improvement for Novice Designers

Lydia B. Chilton, Ecenaz Jen Ozmen, Sam H. Ross, Vivian Liu

2021Year
21Citations
9Top-tier citations

Abstract

Fig. 1. Two examples of how the VisiFit system can improve a visual blend prototype in under 4 minutes. The left image blends New York City and autumn. The right image blends navel orange and winter.

Visual blends are a graphic design challenge to seamlessly integrate two objects into one. Existing tools help novices create prototypes of blends, but it is unclear how they would improve them to be higher fidelity. To help novices, we aim to add structure to the iterative improvement process. We introduce a technique for improving blends called fundamental dimension decomposition. It is grounded in principles of human visual object recognition. We present VisiFit -a computational design system that uses this technique to enable novice graphic designers to improve blends by exploring a structured design space with computationally generated options they can select, adjust, and chain together. Our evaluation shows novices can substantially improve 76% of blends in under 4 minutes. We discuss how the technique can be generalized to other blending problems, and how computational tools can support novices by enabling them to explore a structured design space quickly and efficiently.

CCS Concepts: • Human-centered computing → Interactive systems and tools.

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