Statics Aware Grid Shells

We introduce a framework for the generation of polygonal gridshell architectural structures, whose topology is designed in order to excel in static performances. We start from the analysis of stress on the input surface and we use the resulting tensor field to induce an anisotropic nonEuclidean metric over it. This metric is derived by studying the relation between the stress tensor over a continuous shell and the optimal shape of polygons in a corresponding gridshell. Polygonal meshes with uniform density and isotropic cells under this metric exhibit variable density and anisotropy in Euclidean space, thus achieving a better distribution of the strain energy over their elements. Meshes are further optimized taking into account symmetry and regularity of cells to improve aesthetics. We experiment with quad meshes and hexdominant meshes, demonstrating that our gridshells achieve better static performances than stateoftheart gridshells.     

Automatic generation algorithm of expected results for testing of component-based software system

ContextA component-based software (CBS) system is a typical example of a composite component, which is composed of two or more atomic components. In the test of a CBS system, it is necessary to automatically generate expected results because they are compared with the actual results.ObjectiveThis paper proposes an automatic generation algorithm of expected results for the testing of a CBS system.MethodThe algorithm analyzes Input/Output (I/O) relationships of a CBS system to identify inputs that influence its outputs. Then, the algorithm uses test cases of atomic components for each input and automatically generates expected results. To evaluate the proposed approach, we compare the proposed approach with the other I/O relationship based approach via two case studies which are the CBS systems for guide robot. The comparison shows the effectiveness of our approach.ResultsTo verify effectiveness of the proposed approach, we measure the cost of manual generation of expected results for each case study. The costs are from 0.001 to 0.015 in the first case study, and are from 0.590 to 0.998 in the second case study.ConclusionThis proposed approach reduces the time-consuming and error-prone task which manually generates expected results for the testing of a CBS system.     

基于I~2C总线的云台电机控制系统设计

本文分析了I2 C的工作原理和Linux的I2 C总线驱动程序,构建了高速公路视频监控系统下基于I2 C云台电机控制系统,完成了基于ARM和Linux的I2 C驱动程序、I2 C应用程序和云台电机控制应用程序设计,实现了应用程序控制云台电机,并应用于高速公路视频监控系统中,达到全方位的高速公路视频监控,具有良好的效果和较高的应用价值。     

Physically Meaningful Rendering using Tristimulus Colours

In photorealistic image synthesis the radiative transfer equation is often not solved by simulating every wavelength of light, but instead by computing tristimulus transport, for instance using sRGB primaries as a basis. This choice is convenient, because input texture data is usually stored in RGB colour spaces. However, there are problems with this approach which are often overlooked or ignored. By comparing to spectral reference renderings, we show how rendering in tristimulus colour spaces introduces colour shifts in indirect light, violation of energy conservation, and unexpected behaviour in participating media. Furthermore, we introduce a fast method to compute spectra from almost any given XYZ input colour. It creates spectra that match the input colour precisely. Additionally, like in natural reflectance spectra, their energy is smoothly distributed over wide wavelength bands. This method is both useful to upsample RGB input data when spectral transport is used and as an intermediate step for corrected tristimulus‐based transport. Finally, we show how energy conservation can be enforced in RGB by mapping colours to valid reflectances.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Photoelasticity Raycasting

We present a novel physically‐based method to visualize stress tensor fields. By incorporating photoelasticity into traditional raycasting and extending it with reflection and refraction, taking into account polarization, we obtain the virtual counterpart to traditional experimental polariscopes. This allows us to provide photoelastic analysis of stress tensor fields in arbitrary domains. In our model, the optical material properties, such as stress‐optic coefficient and refractive index, can either be chosen in compliance with the subject under investigation, or, in case of stress problems that do not model optical properties or that are not transparent, be chosen according to known or even new transparent materials. This enables direct application of established polariscope methodology together with respective interpretation. Using a GPU‐based implementation, we compare our technique to experimental data, and demonstrate its utility with several simulated datasets.     

Persistent Homology for the Evaluation of Dimensionality Reduction Schemes

High‐dimensional data sets are a prevalent occurrence in many application domains. This data is commonly visualized using dimensionality reduction (DR) methods. DR methods provide e.g. a two‐dimensional embedding of the abstract data that retains relevant high‐dimensional characteristics such as local distances between data points. Since the amount of DR algorithms from which users may choose is steadily increasing, assessing their quality becomes more and more important. We present a novel technique to quantify and compare the quality of DR algorithms that is based on persistent homology. An inherent beneficial property of persistent homology is its robustness against noise which makes it well suited for real world data. Our pipeline informs about the best DR technique for a given data set and chosen metric (e.g. preservation of local distances) and provides knowledge about the local quality of an embedding, thereby helping users understand the shortcomings of the selected DR method. The utility of our method is demonstrated using application data from multiple domains and a variety of commonly used DR methods.     

Woodification: User‐Controlled Cambial Growth Modeling

We present a botanical simulation of secondary (cambial) tree growth coupled to a physical cracking simulation of its bark. Whereas level set growth would use a fixed resolution voxel grid, our system extends the deformable simplicial complex (DSC), supporting new biological growth functions robustly on any surface polygonal mesh with adaptive subdivision, collision detection and topological control. We extend the DSC with temporally coherent texturing, and surface cracking with a user‐controllable biological model coupled to the stresses introduced by the cambial growth model.     

A Dimension‐reduced Pressure Solver for Liquid Simulations

This work presents a method for efficiently simplifying the pressure projection step in a liquid simulation. We first devise a straightforward dimension reduction technique that dramatically reduces the cost of solving the pressure projection. Next, we introduce a novel change of basis that satisfies free‐surface boundary conditions exactly, regardless of the accuracy of the pressure solve. When combined, these ideas greatly reduce the computational complexity of the pressure solve without compromising free surface boundary conditions at the highest level of detail. Our techniques are easy to parallelize, and they effectively eliminate the computational bottleneck for large liquid simulations.