The physical properties of objects cannot typically be adjusted post-fabrication to meet specific needs or preferences. While 3D printing offers the potential of design-time customization, manipulating object properties after the object has been printed remains challenging. We present a 3D printable bistable mechanism with an actuation force that can be quickly and repeatedly adjusted after fabrication by up to a factor of 5.25, enabling tunable monostable or bistable behavior. Our mechanism, printable on commodity low-cost 3D printers, incorporates off-the-shelf elastic threads to maintain robust operation when fabricated at different sizes. We present an evaluation of how manipulating geometric parameters influences the post-print behavior of our design and demonstrate its versatility in five functional objects.

We revisit the statistical foundation of the celebrated context tree weighting (CTW) algorithm, and we develop a Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, along with an associated collection of methodological tools for exact inference for discrete time series. In addition to deterministic algorithms that learn the a posteriori most likely models and compute their posterior probabilities, we introduce a family of variable-dimension Markov chain Monte Carlo samplers, facilitating further exploration of the posterior. The performance of the proposed methods in model selection, Markov order estimation and prediction is illustrated through simulation experiments and real-world applications.

We present a novel haptic and audio feedback device that allows blind and visually impaired (BVI) users to understand circuit diagrams. TangibleCircuits allows users to interact with a 3D printed tangible model of a circuit which provides audio tutorial directions while being touched. Our system comprises an automated parsing algorithm which extracts 3D printable models as well as an audio interfaces from a Fritzing diagram. To better understand the requirements of designing technology to assist BVI users in learning hardware computing, we conducted a series of formative inquiries into the accessibility limitations of current circuit tutorial technologies. In addition, we derived insights and design considerations gleaned from conducting a formal comparative user study to understand the effectiveness of TangibleCircuits as a tutorial system. We found that BVI users were better able to understand the geometric, spatial and structural circuit information using TangibleCircuits, as well as enjoyed learning with our tool.

Members of the blind and visually impaired community rely heavily on tactile illustrations - raised line graphics on paper that are felt by hand - to understand geometric ideas in school textbooks, depict a story in children's books, or conceptualize exhibits in museums. However, these illustrations often fail to achieve their goals, in large part due to the lack of understanding in how 3D shapes can be represented in 2D projections. This paper describes a new technique to design tactile illustrations considering the needs of blind individuals. Successful illustration design of 3D objects presupposes identification and combination of important information in topology and geometry. We propose a twofold approach to improve shape understanding. First, we introduce a part-based multi-projection rendering strategy to display geometric information of 3D shapes, making use of canonical viewpoints and removing reliance on traditional perspective projections. Second, curvature information is extracted from cross sections and embedded as textures in our illustrations.

Abstract Watercolor paintings have a unique look that mixes subtle color gradients and sophisticated diffusion patterns. This makes them immediately recognizable and gives them a unique appeal. Creating such paintings requires advanced skills that are beyond the reach of most people. Even for trained artists, producing several copies of a painting is a tedious task. One can resort to scanning an existing painting and printing replicas, but these are all identical and have lost an essential characteristic of a painting, its uniqueness. We address these two issues with a technique to fabricate woodblocks that we later use to create watercolor prints. The woodblocks can be reused to produce multiple copies but each print is unique due to the physical process that we introduce. We also design an image processing pipeline that helps users to create the woodblocks and describe a protocol that produces prints by carefully controlling the interplay between the paper, ink pigments, and water so that the final piece depicts the desired scene while exhibiting the distinctive features of watercolor. Our technique enables anyone with the resources to produce watercolor prints.

This paper presents an interactive design interface for three-dimensional free-form musical wind instruments. The sound of a wind instrument is governed by the acoustic resonance as a result of complicated interactions of sound waves and internal geometries of the instrument. Thus, creating an original free-form wind instrument by manual methods is a challenging problem. Our interface provides interactive sound simulation feedback as the user edits, allowing exploration of original wind instrument designs. Sound simulation of a 3D wind musical instrument is known to be computationally expensive. To overcome this problem, we first model the wind instruments as a passive resonator, where we ignore coupled oscillation excitation from the mouthpiece. Then we present a novel efficient method to estimate the resonance frequency based on the boundary element method by formulating the resonance problem as a minimum eigenvalue problem. Furthermore, we can efficiently compute an approximate resonance frequency using a new technique based on a generalized eigenvalue problem. The designs can be fabricated using a 3D printer, thus we call the results "print-wind instruments" in association with woodwind instruments. We demonstrate our approach with examples of unconventional shapes performing familiar songs.

This paper introduces a perceptual model for determining 3D printing orientations. Additive manufacturing methods involving low-cost 3D printers often require robust branching support structures to prevent material collapse at overhangs. Although the designed shape can successfully be made by adding supports, residual material remains at the contact points after the supports have been removed, resulting in unsightly surface artifacts. Moreover, fine surface details on the fabricated model can easily be damaged while removing supports. To prevent the visual impact of these artifacts, we present a method to find printing directions that avoid placing supports in perceptually significant regions. Our model for preference in 3D printing direction is formulated as a combination of metrics including area of support, visual saliency, preferred viewpoint and smoothness preservation. We develop a training-and-learning methodology to obtain a closed-form solution for our perceptual model and perform a large-scale study. We demonstrate the performance of this perceptual model on both natural and man-made objects.