Polarized light mosaics (PLMs) are color-changing structures that alter their appearance based on the orientation of incident polarized light. While a few artists have developed techniques for crafting PLMs by hand, the underlying material properties are difficult to reason about; there exist no tools to bridge the high-level design objectives with the low-level physics knowledge needed to create PLMs. In this paper, we introduce the first system for creating Polagons: machine-made PLMs crafted from cellophane with user-defined color changing behaviors. Our system includes an interface for designing and visualizing Polagons as well as a fabrication process based on laser cutting and welding that requires minimal assembly by the user. We define the design space for Polagons and demonstrate how formalizing the process for creating PLMs can enable new applications in fields such as education, data visualization, and fashion.

Designers of machine-cut objects must often consider whether and how their design can be fabricated with their available materials. In contrast to tools that support preparing finished designs for fabrication, we investigate shortening the feedback loop between design creation and fabrication preparation. To this end, we present Fabricaide, a fabrication-aware tool that interleaves the processes of creating and preparing designs for fabrication. By providing live feedback on how parts should be placed onto material sheets, analyzing how much material is consumed, and alerting users when designs are infeasible, Fabricaide enables users to proactively tailor their design to their available material. Fabricaide achieves this with a custom packing algorithm that arranges parts onto material sheets at interactive speeds. Our qualitative user study shows how Fabricaide can support different workflows, encourage material-conscious design practices, and provide insights on how to further improve similar interfaces in the future.

We present Sprayable User Interfaces: room-sized interactive surfaces that contain sensor and display elements created by airbrushing functional inks. Since airbrushing is inherently mobile, designers can create large-scale user interfaces on complex 3D geometries where existing stationary fabrication methods fail. To enable Sprayable User Interfaces, we developed a novel design and fabrication pipeline that takes a desired user interface layout as input and automatically generates stencils for airbrushing the layout onto a physical surface. After fabricating stencils from cardboard or projecting stencils digitally, designers spray each layer with an airbrush, attach a microcontroller to the user interface, and the interface is ready to be used. Our technical evaluation shows that Sprayable User Interfaces work on various geometries and surface materials, such as porous stone and rough wood. We demonstrate our system with several application examples including interactive smart home applications on a wall and a soft leather sofa, an interactive smart city application, and interactive architecture in public office spaces.

We present CATS, a digital painting system that synthesizes textures from live video in real-time, short-cutting the typical brush- and texture- gathering workflow. Through the use of boundary-aware texture synthesis, CATS produces strokes that are non-repeating and blend smoothly with each other. This allows CATS to produce paintings that would be difficult to create with traditional art supplies or existing software. We evaluated the effectiveness of CATS by asking artists to integrate the tool into their creative practice for two weeks; their paintings and feedback demonstrate that CATS is an expressive tool which can be used to create richly textured paintings.

Improving mobile keyboard typing speed increases in value as more tasks move to a mobile setting. Autocorrect reduces the time it takes to manually fix typing errors, which results in typing speed increase. However, recent user studies uncovered an unexplored side-effect: participants' aversion to typing errors despite autocorrect. We present a computational model of typing on keyboards with autocorrect, which enables precise study of expert typists' aversion to typing errors on such keyboards. Unlike empirical typing studies that last days, our model evaluates this phenomenon for any autocorrect accuracy in seconds. We show that typists' aversion to typing errors imposes a limit on upper bound typing speeds, even for highly accurate autocorrect. Our findings motivate future keyboard designs that reduce typists' aversion to typing errors to increase typing speeds.

Knitting creates complex, soft fabrics with unique texture properties that can be used to create interactive objects.However, little work addresses the challenges of designing and using knitted textures computationally. We present KnitPick: a pipeline for interpreting hand-knitting texture patterns into KnitGraphs which can be output to machine and hand-knitting instructions. Using KnitPick, we contribute a measured and photographed data set of 472 knitted textures. Based on findings from this data set, we contribute two algorithms for manipulating KnitGraphs. KnitCarving shapes a graph while respecting a texture, and KnitPatching combines graphs with disparate textures while maintaining a consistent shape. KnitPick is the first system to bridge the gap between hand- and machine-knitting when creating complex knitted textures.