Modern 3D printers are capable of printing large-size light-field displays at high-resolutions. However, optimizing such displays in full 3D volume for a given light-field imagery is still a challenging task. Existing light field displays optimize over relatively small resolutions using a few co-planar layers in a 2.5D fashion to keep the problem tractable. In this paper, we propose a novel end-to-end optimization approach that encodes input light field imagery as a continuous-space implicit representation in a neural network. This allows fabricating high-resolution, attenuation-based volumetric displays that exhibit the target light fields. In addition, we incorporate the physical constraints of the material to the optimization such that the result can be printed in practice. Our simulation experiments demonstrate that our approach brings significant visual quality improvement compared to the multilayer and uniform grid-based approaches. We validate our simulations with fabricated prototypes and demonstrate that our pipeline is flexible enough to allow fabrications of both planar and non-planar displays.

https://dl.acm.org/doi/pdf/10.1145/3414685.3417879

Neural light field 3D printing

Lenticular prints are a popular medium for producing automultiscopic glasses-free 3D images. The light field emitted by such prints has a fixed spatial and angular resolution. We increase both perceived angular and spatial resolution by modifying the lenslet array to better match the content of a given light field. Our optimization algorithm analyzes the input light field and computes an optimal lenslet size, shape, and arrangement that best matches the input light field given a set of output parameters. The resulting emitted light field shows higher detail and smoother motion parallax compared to fixed-size lens arrays. We demonstrate our technique using rendered simulations and by 3D printing lens arrays, and we validate our approach in simulation with a user study.

Content-adaptive lenticular prints

Moire is an appealing visual effect observable when two or more repetitive patterns are superposed. Fabrication of moire effects has already proven to be useful in a range of applications, from art to engineering. Here, we introduce a method for designing and fabricating level-line moires on curved surfaces. These moire shapes are obtained by superposing a partly absorbing layer and a layer formed by an array of cylindrical lenses or by two layers of cylindrical lenses. We formulate the problem of placing an array of cylindrical lenses on a curved surface as a design problem with a small number of dimensions. The range of possible solutions can therefore be explored by a human observer. We demonstrate the quality of our method by rendered simulations and by fabrication. The resulting static displays can be manufactured using different fabrication techniques, from multi-material 3D printing to molding.

Fabrication of moiré on curved surfaces.

Wearable robotic arms (WRA) open up a unique interaction space that closely integrates the user’s body with an embodied robotic collaborator. This space affords diverse interaction styles, including body movement, hand gestures, or gaze. Yet, it is so-far unexplored which commands are desirable from a user perspective. Contributing findings from an elicitation study (N=14), we provide a comprehensive set of interactions for basic robot control, navigation, object manipulation, and emergency situations, performed when hands are free or occupied. Our study provides insights into preferred body parts, input modalities, and the users’ underlying sources of inspiration. Comparing interaction styles between WRAs and off-body robots, we highlight how WRAs enable a range of interactions specific for on-body robots and how users use WRAs both as tools and as collaborators. We conclude by providing guidance on the design of ad-hoc interaction with WRAs informed by user behavior.

/pdf/i-need-a-third-arm-eliciting-body-based-interactions-with-a-2bzyq7or.pdf

Artin Saberpour

Papers

Fabrication of moiré on curved surfaces.

I Need a Third Arm! Eliciting Body-based Interactions with a Wearable Robotic Arm