Yonghao Yue

Wire mesh design

We present a computational approach for designing wire meshes, i.e., freeform surfaces composed of woven wires arranged in a regular grid. To facilitate shape exploration, we map material properties of wire meshes to the geometric model of Chebyshev nets. This abstraction is exploited to build an efficient optimization scheme. While the theory of Chebyshev nets suggests a highly constrained design space, we show that allowing controlled deviations from the underlying surface provides a rich shape space for design exploration. Our algorithm balances globally coupled material constraints with aesthetic and geometric design objectives that can be specified by the user in an interactive design session. In addition to sculptural art, wire meshes represent an innovative medium for industrial applications including composite materials and architectural façades. We demonstrate the effectiveness of our approach using a variety of digital and physical prototypes with a level of shape complexity unobtainable using previous methods.

Unbiased, adaptive stochastic sampling for rendering inhomogeneous participating media

Realistic rendering of participating media is one of the major subjects in computer graphics. Monte Carlo techniques are widely used for realistic rendering because they provide unbiased solutions, which converge to exact solutions. Methods based on Monte Carlo techniques generate a number of light paths, each of which consists of a set of randomly selected scattering events. Finding a new scattering event requires free path sampling to determine the distance from the previous scattering event, and is usually a time-consuming process for inhomogeneous participating media. To address this problem, we propose an adaptive and unbiased sampling technique using kd-tree based space partitioning. A key contribution of our method is an automatic scheme that partitions the spatial domain into sub-spaces (partitions) based on a cost model that evaluates the expected sampling cost. The magnitude of performance gain obtained by our method becomes larger for more inhomogeneous media, and rises to two orders compared to traditional free path sampling techniques.

An inverse problem approach for automatically adjusting the parameters for rendering clouds using photographs

Clouds play an important role in creating realistic images of outdoor scenes. Many methods have therefore been proposed for displaying realistic clouds. However, the realism of the resulting images depends on many parameters used to render them and it is often difficult to adjust those parameters manually. This paper proposes a method for addressing this problem by solving an inverse rendering problem: given a non-uniform synthetic cloud density distribution, the parameters for rendering the synthetic clouds are estimated using photographs of real clouds. The objective function is defined as the difference between the color histograms of the photograph and the synthetic image. Our method searches for the optimal parameters using genetic algorithms. During the search process, we take into account the multiple scattering of light inside the clouds. The search process is accelerated by precomputing a set of intermediate images. After ten to twenty minutes of precomputation, our method estimates the optimal parameters within a minute.

Pixel Art with Refracted Light by Rearrangeable Sticks

Pixel art is a kind of digital art that through per‐pixel manipulation enables production of a diverse array of artistic images. In this paper, we present a new way for people to experience and express pixel art. Our digital art consists of a set of sticks made of acrylate resin, each of which refracts light from a parallel light source, in certain directions. Artistic users are able to easily rearrange these sticks and view their digital art through the refracted light projection on any planar surface. As we demonstrate in this paper, a user can generate various artistic images using only a single set of sticks. We additionally envision that our pixel art with rearrangeable sticks would have great entertainment appeal, e.g., as an art puzzle.

Continuum Foam: A Material Point Method for Shear-Dependent Flows

We consider the simulation of dense foams composed of microscopic bubbles, such as shaving cream and whipped cream. We represent foam not as a collection of discrete bubbles, but instead as a continuum. We employ the material point method (MPM) to discretize a hyperelastic constitutive relation augmented with the Herschel-Bulkley model of non-Newtonian viscoplastic flow, which is known to closely approximate foam behavior. Since large shearing flows in foam can produce poor distributions of material points, a typical MPM implementation can produce non-physical internal holes in the continuum. To address these artifacts, we introduce a particle resampling method for MPM. In addition, we introduce an explicit tearing model to prevent regions from shearing into artificially thin, honey-like threads. We evaluate our methods efficacy by simulating a number of dense foams, and we validate our method by comparing to real-world footage of foam.

Regrasping and unfolding of garments using predictive thin shell modeling

Deformable objects such as garments are highly unstructured, making them difficult to recognize and manipulate. In this paper, we propose a novel method to teach a two-arm robot to efficiently track the states of a garment from an unknown state to a known state by iterative regrasping. The problem is formulated as a constrained weighted evaluation metric for evaluating the two desired grasping points during regrasping, which can also be used for a convergence criterion The result is then adopted as an estimation to initialize a regrasping, which is then considered as a new state for evaluation. The process stops when the predicted thin shell conclusively agrees with reconstruction. We show experimental results for regrasping a number of different garments including sweater, knitwear, pants, and leggings, etc.

Folding deformable objects using predictive simulation and trajectory optimization

Robotic manipulation of deformable objects remains a challenging task. One such task is folding a garment autonomously. Given start and end folding positions, what is an optimal trajectory to move the robotic arm to fold a garment? Certain trajectories will cause the garment to move, creating wrinkles, and gaps, other trajectories will fail altogether. We present a novel solution to find an optimal trajectory that avoids such problematic scenarios. The trajectory is optimized by minimizing a quadratic objective function in an off-line simulator, which includes material properties of the garment and frictional force on the table. The function measures the dissimilarity between a user folded shape and the folded garment in simulation, which is then used as an error measurement to create an optimal trajectory. We demonstrate that our two-arm robot can follow the optimized trajectories, achieving accurate and efficient manipulations of deformable objects.

Poisson-Based Continuous Surface Generation for Goal-Based Caustics

We present a technique for computing the shape of a transparent object that can generate user-defined caustic patterns. The surface of the object generated using our method is smooth. Thanks to this property, the resulting caustic pattern is smooth, natural, and highly detailed compared to the results btained using previous methods. Our method consists of two processes. First, we use a differential geometry approach to compute a smooth mapping between the distributions of the incident light and the light reaching the screen. Second, we utilize this mapping to compute the surface of the object. We solve Poissons equation to compute both the mapping and the surface of the object.

Legolization: optimizing LEGO designs

Building LEGO sculptures requires accounting for the target objects shape, colors, and stability. In particular, finding a good layout of LEGO bricks that prevents the sculpture from collapsing (due to its own weight) is usually challenging, and it becomes increasingly difficult as the target object becomes larger or more complex. We devise a force-based analysis for estimating physical stability of a given sculpture. Unlike previous techniques for Legolization, which typically use heuristic-based metrics for stability estimation, our force-based metric gives 1) an ordering in the strength so that we know which structure is more stable, and 2) a threshold for stability so that we know which one is stable enough. In addition, our stability analysis tells us the weak portion of the sculpture. Building atop our stability analysis, we present a layout refinement algorithm that iteratively improves the structure around the weak portion, allowing for automatic generation of a LEGO brick layout from a given 3D model, accounting for color information, required workload (in terms of the number of bricks) and physical stability. We demonstrate the success of our method with real LEGO sculptures built up from a wide variety of 3D models, and compare against previous methods.

Global Illumination for Interactive Lighting Design Using Light Path Pre-Computation and Hierarchical Histogram Estimation

In this paper, we propose a fast global illumination solution for interactive lighting design. Using our method, light sources and the viewpoint are movable, and the characteristics of materials can be modified (assuming low-frequency BRDF) during rendering. Our solution is based on particle tracing (a variation of photon mapping) and final gathering. We assume that objects in the input scene are static, and pre-compute potential light paths for particle tracing and final gathering. To perform final gathering fast, we propose an efficient technique called Hierarchical Histogram Estimation for rapid estimation of radiances from the distribution of the particles. The rendering process of our method can be fully implemented on the GPU and our method achieves interactive frame rates for rendering scenes with even more than 100,000 triangles.We describe a new algorithm for the visualisation of implicit algebraic curves, which isolates the singular points, compute the topological degree around these points in order to check that the topology of the curve can be deduced from the points on the boundary of these singular regions. The other regions are divided into x or y regular regions, in which the branches of the curve are also determined from information on the boundary. Combined with enveloping techniques of the polynomial represented in the Bernstein basis, it is shown on examples that this algorithm is able to render curves defined by high degree polynomials with large coefficients, to identify regions of interest and to zoom safely on these regions.