VisiFit: Structuring Iterative Improvement for Novice Designers
Lydia B. Chilton, Ecenaz Jen Ozmen, Sam H Ross, Vivian Liu
Abstract
Visual blends are an advanced graphic design technique 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 method for improving prototypes that uses secondary design dimensions to explore a structured design space. This method is grounded in the cognitive principles of human visual object recognition. We present VisiFit – a computational design system that uses this method to enable novice graphic designers to improve blends 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 method 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.