SIGGRAPH 2015 论文列表

Furniture typically consists of assemblies of elongated and planar parts that are connected together by glue, nails, hinges, screws, or other means that do not encourage disassembly and re-assembly. An alternative approach is to use an interlocking mechanism, where the component parts tightly interlock with one another. The challenge in designing such a network of interlocking joints is that local analysis is insufficient to guarantee global interlocking, and there is a huge number of joint combinations that require an enormous exploration effort to ensure global interlocking. In this paper, we present a computational solution to support the design of a network of interlocking joints that form a globally-interlocking furniture assembly. The key idea is to break the furniture complex into an overlapping set of small groups, where the parts in each group are immobilized by a local key, and adjacent groups are further locked with dependencies. The dependency among the groups saves the effort of exploring the immobilization of every subset of parts in the assembly, thus allowing the intensive interlocking computation to be localized within each small group. We demonstrate the effectiveness of our technique on many globally-interlocking furniture assemblies of various shapes and complexity.

Hydrographic printing is a well-known technique in industry for transferring color inks on a thin film to the surface of a manufactured 3D object. It enables high-quality coloring of object surfaces and works with a wide range of materials, but suffers from the inability to accurately register color texture to complex surface geometries. Thus, it is hardly usable by ordinary users with customized shapes and textures. We present computational hydrographic printing , a new method that inherits the versatility of traditional hydrographic printing, while also enabling precise alignment of surface textures to possibly complex 3D surfaces. In particular, we propose the first computational model for simulating hydrographic printing process. This simulation enables us to compute a color image to feed into our hydrographic system for precise texture registration. We then build a physical hydrographic system upon off-the-shelf hardware, integrating virtual simulation, object calibration and controlled immersion. To overcome the difficulty of handling complex surfaces, we further extend our method to enable multiple immersions, each with a different object orientation, so the combined colors of individual immersions form a desired texture on the object surface. We validate the accuracy of our computational model through physical experiments, and demonstrate the efficacy and robustness of our system using a variety of objects with complex surface textures.

We present the first computational method that allows ordinary users to create complex twisty joints and puzzles inspired by the Rubik's Cube mechanism. Given a user-supplied 3D model and a small subset of rotation axes, our method automatically adjusts those rotation axes and adds others to construct a "non-blocking" twisty joint in the shape of the 3D model. Our method outputs the shapes of pieces which can be directly 3D printed and assembled into an interlocking puzzle. We develop a group-theoretic approach to representing a wide class of twisty puzzles by establishing a connection between non-blocking twisty joints and the finite subgroups of the rotation group SO(3). The theoretical foundation enables us to build an efficient system for automatically completing the set of rotation axes and fast collision detection between pieces. We also generalize the Rubik's Cube mechanism to a large family of twisty puzzles.

We present a new approach for the reproduction of color images on a metallic substrate that look bright and colorful under specular reflection observation conditions and also look good under non-specular reflection observation conditions. We fit amounts of both the white ink and the classical cyan, magenta and yellow inks according to a formula optimizing the reproduction of colors simultaneously under specular and non-specular observation conditions. In addition, we can hide patterns such as text or graphical symbols in one viewing mode, specular or non-specular, and reveal them in the other viewing mode. We rely on the trade-off between amounts of white diffuse ink and amounts of cyan, magenta and yellow inks to control lightness in specular and in non-specular observation conditions. Further effects are grayscale images that alternate from a first image to a second independent image when tilting the print from specular to non-specular reflection observation conditions. Applications comprise art and entertainment, publicity, posters, as well as document security.

We present a novel method to simulate codimensional non-Newtonian fluids on simplicial complexes. Our method extends previous work for codimensional incompressible flow to various types of non-Newtonian fluids including both shear thinning and thickening, Bingham plastics, and elastoplastics. We propose a novel time integration scheme for semi-implicitly treating elasticity, which when combined with a semi-implicit method for variable viscosity alleviates the need for small time steps. Furthermore, we propose an improved treatment of viscosity on the rims of thin fluid sheets that allows us to capture their elusive, visually appealing twisting motion. In order to simulate complex phenomena such as the mixing of colored paint, we adopt a multiple level set framework and propose a discretization on simplicial complexes that facilitates the tracking of material interfaces across codimensions. We demonstrate the efficacy of our approach by simulating a wide variety of non-Newtonian fluid phenomena exhibiting various codimensional features.

Several techniques exist to automatically synthesize a 2D image resembling an input exemplar texture. Most of the approaches optimize a new image so that the color neighborhoods in the output closely match those in the input, across all scales. In this paper we revisit by-example texture synthesis in the context of additive manufacturing. Our goal is to generate not only colors, but also structure along output surfaces: given an exemplar indicating 'solid' and 'empty' pixels, we generate a similar pattern along the output surface. The core challenge is to guarantee that the pattern is not only fully connected, but also structurally sound. To achieve this goal we propose a novel formulation for on-surface by-example texture synthesis that directly works in a voxel shell around the surface. It enables efficient local updates to the pattern, letting our structural optimizer perform changes that improve the overall rigidity of the pattern. We use this technique in an iterative scheme that jointly optimizes for appearance and structural soundness. We consider fabricability constraints and a user-provided description of a force profile that the object has to resist. Our results fully exploit the capabilities of additive manufacturing by letting users design intricate structures along surfaces. The structures are complex, yet they resemble input exemplars, resulting in a modeling tool accessible to casual users.

The tendons of the hand and other biomechanical systems form a complex network of sheaths, pulleys, and branches. By modeling these anatomical structures, we obtain realistic simulations of coordination and dynamics that were previously not possible. First, we introduce Eulerian-on-Lagrangian discretization of tendon strands, with a new selective quasistatic formulation that eliminates unnecessary degrees of freedom in the longitudinal direction, while maintaining the dynamic behavior in transverse directions. This formulation also allows us to take larger time steps. Second, we introduce two control methods for biomechanical systems: first, a general-purpose learning-based approach requiring no previous system knowledge, and a second approach using data extracted from the simulator. We use various examples to compare the performance of these controllers.

We present a fully automatic method for generating guaranteed bijective surface parameterizations from triangulated 3D surfaces partitioned into charts. We do so by using a distortion metric that prevents local folds of triangles in the parameterization and a barrier function that prevents intersection of the chart boundaries. In addition, we show how to modify the line search of an interior point method to directly compute the singularities of the distortion metric and barrier functions to maintain a bijective map. By using an isometric metric that is efficient to compute and a spatial hash to accelerate the evaluation and gradient of the barrier function for the boundary, we achieve fast optimization times. Unlike previous methods, we do not require the boundary be constrained by the user to a non-intersecting shape to guarantee a bijection, and the boundary of the parameterization is free to change shape during the optimization to minimize distortion.

Designers frequently draw curvature lines to convey bending of smooth surfaces in concept sketches. We present a method to extrapolate curvature lines in a rough concept sketch, recovering the intended 3D curvature field and surface normal at each pixel of the sketch. This 3D information allows to enrich the sketch with 3D-looking shading and texturing. We first introduce the concept of regularized curvature lines that model the lines designers draw over curved surfaces, encompassing curvature lines and their extension as geodesics over flat or umbilical regions. We build on this concept to define the orthogonal cross field that assigns two regularized curvature lines to each point of a 3D surface. Our algorithm first estimates the projection of this cross field in the drawing, which is nonorthogonal due to foreshortening. We formulate this estimation as a scattered interpolation of the strokes drawn in the sketch, which makes our method robust to sketchy lines that are typical for design sketches. Our interpolation relies on a novel smoothness energy that we derive from our definition of regularized curvature lines. Optimizing this energy subject to the stroke constraints produces a dense nonorthogonal 2D cross field which we then lift to 3D by imposing orthogonality. Thus, one central concept of our approach is the generalization of existing cross field algorithms to the nonorthogonal case. We demonstrate our algorithm on a variety of concept sketches with various levels of sketchiness. We also compare our approach with existing work that takes clean vector drawings as input.

We consider the problem of obtaining a recognizable shape as superposition moiré of two line gratings. The method we propose generates moiré lines located between the shape foreground and background centers and the shape boundaries. Upon relative displacement of the superposed base- and revealing-layer gratings, the moiré lines move and give the impression of beating shapes. Original bilevel shapes are converted into elevation profiles that are embedded by small local shifts within the base-layer grating layout. The elevation profile's level lines are revealed as moiré by superposing the base and revealing layers. Similar level line moirés can be obtained by applying an identical geometric transformation to both the base and the revealing layers. In order to create grayscale or color images embedding several distinct moiré shapes, we create as base layer a dither array made of several ditherband gratings, each one embedding its specific elevation profile. Further variants include the possibility of incorporating elevation profiles within both the base and the revealing layers, or having two elevation profiles sharing a same base layer by tiling the available space. The moiré-level line techniques can be advantageously used for decorative or for anti-counterfeiting applications. Their base- and revealing-layer gratings may be produced by printing techniques, by imaging on film, or by arrays of cylindrical microlenses.

We introduce music-driven video montage, a media format that offers a pleasant way to browse or summarize video clips collected from various occasions, including gatherings and adventures. In music-driven video montage, the music drives the composition of the video content. According to musical movement and beats, video clips are organized to form a montage that visually reflects the experiential properties of the music. Nonetheless, it takes enormous manual work and artistic expertise to create it. In this paper, we develop a framework for automatically generating music-driven video montages. The input is a set of video clips and a piece of background music. By analyzing the music and video content, our system extracts carefully designed temporal features from the input, and casts the synthesis problem as an optimization and solves the parameters through Markov Chain Monte Carlo sampling. The output is a video montage whose visual activities are cut and synchronized with the rhythm of the music, rendering a symphony of audio-visual resonance.

Recent digital fabrication tools have opened up accessibility to personalized rapid prototyping; however, such tools are limited to product-scale objects. The materials currently available for use in 3D printing are too fine for large-scale objects, and CNC gantry sizes limit the scope of printable objects. In this paper, we propose a new method for printing architecture-scale objects. Our proposal includes three developments: (i) a construction material consisting of chopsticks and glue, (ii) a handheld chopstick dispenser, and (iii) a printing guidance system that uses projection mapping. The proposed chopstickglue material is cost effective, environmentally sustainable, and can be printed more quickly than conventional materials. The developed handheld dispenser enables consistent feeding of the chopstickglue material composite. The printing guidance system --- consisting of a depth camera and a projector --- evaluates a given shape in real time and indicates where humans should deposit chopsticks by projecting a simple color code onto the form under construction. Given the mechanical specifications of the stickglue composite, an experimental pavilion was designed as a case study of the proposed method and built without scaffoldings and formworks. The case study also revealed several fundamental limitations, such as the projector does not work in daylight, which requires future investigations.

Dressing is one of the most common activities in human society. Perfecting the skill of dressing can take an average child three to four years of daily practice. The challenge is primarily due to the combined difficulty of coordinating different body parts and manipulating soft and deformable objects (clothes). We present a technique to synthesize human dressing by controlling a human character to put on an article of simulated clothing. We identify a set of primitive actions which account for the vast majority of motions observed in human dressing. These primitive actions can be assembled into a variety of motion sequences for dressing different garments with different styles. Exploiting both feed-forward and feedback control mechanisms, we develop a dressing controller to handle each of the primitive actions. The controller plans a path to achieve the action goal while making constant adjustments locally based on the current state of the simulated cloth when necessary. We demonstrate that our framework is versatile and able to animate dressing with different clothing types including a jacket, a pair of shorts, a robe, and a vest. Our controller is also robust to different cloth mesh resolutions which can cause the cloth simulator to generate significantly different cloth motions. In addition, we show that the same controller can be extended to assistive dressing.

Identifying sparse salient structures from dense pixels is a longstanding problem in visual computing. Solutions to this problem can benefit both image manipulation and understanding. In this paper, we introduce an image transform based on theL1norm for piecewise image flattening. This transform can effectively preserve and sharpen salient edges and contours while eliminating insignificant details, producing a nearly piecewise constant image with sparse structures. A variant of this image transform can perform edge-preserving smoothing more effectively than existing state-of-the-art algorithms. We further present a new method for complex scene-level intrinsic image decomposition. Our method relies on the above image transform to suppress surface shading variations, and perform probabilistic reflectance clustering on the flattened image instead of the original input image to achieve higher accuracy. Extensive testing on theIntrinsic-Images-in-the-Wilddatabase indicates our method can perform significantly better than existing techniques both visually and numerically. The obtained intrinsic images have been successfully used in two applications, surface retexturing and 3D object compositing in photographs.