Capillarity-driven dynamics of water–alcohol mixtures in nanofluidic channels

We investigated the spontaneous capillarity-driven filling of nanofluidic channels with a thickness of 6 and 16 nm using mixtures of ethanol and water of variable composition. To improve the visibility of the fluid, we embedded metal mirrors into the top and bottom walls of the channels that act as a Fabry–Pérot interferometer. The motion of propagating liquid–air menisci was monitored for various concentrations in transmission with an optical microscope. In spite of the visible effects of surface roughness and different affinity of water and ethanol to the channel walls, the dynamics followed the classical t ^1/2—dependence according to Lucas and Washburn. While the prefactor of this algebraic relation falls short of the expectations based on bulk properties by 10–30%, the relative variation between mixtures of different composition follows the expectations based on the bulk surface tension and viscosity, implying that—despite the small width of the channels and the large surface-to-volume ratio—specific adsorption or chemical selectivity effects are not relevant. We briefly discuss the impact of surface roughness on our experimental results.     

Vision and Rain

The visual effects of rain are complex. Rain produces sharp intensity changes in images and videos that can severely impair the performance of outdoor vision systems. In this paper, we provide a comprehensive analysis of the visual effects of rain and the various factors that affect it. Based on this analysis, we develop efficient algorithms for handling rain in computer vision as well as for photorealistic rendering of rain in computer graphics. We first develop a photometric model that describes the intensities produced by individual rain streaks and a dynamic model that captures the spatio-temporal properties of rain. Together, these models describe the complete visual appearance of rain. Using these models, we develop a simple and effective post-processing algorithm for detection and removal of rain from videos. We show that our algorithm can distinguish rain from complex motion of scene objects and other time-varying textures. We then extend our analysis by studying how various factors such as camera parameters, rain properties and scene brightness affect the appearance of rain. We show that the unique physical properties of rain—its small size, high velocity and spatial distribution—makes its visibility depend strongly on camera parameters. This dependence is used to reduce the visibility of rain during image acquisition by judiciously selecting camera parameters. Conversely, camera parameters can also be chosen to enhance the visibility of rain. This ability can be used to develop an inexpensive and portable camera-based rain gauge that provides instantaneous rain-rate measurements. Finally, we develop a rain streak appearance model that accounts for the rapid shape distortions (i.e. oscillations) that a raindrop undergoes as it falls. We show that modeling these distortions allows us to faithfully render the complex intensity patterns that are visible in the case of raindrops that are close to the camera.     

多风格融合的复杂森林场景自适应可视化

为了保证森林场景可视化时的真实感,同时保持动态森林场景生成时间的恒定性,本文提出了一种多风格融合的复杂森林场景自适应可视化方法。该方法利用基于视距的模型分布函数来控制树木模型的分布比例,从而建立多风格融合的森林可视化模型;在此基础上,根据复杂森林场景中树木生长模型的计算时间、三维树木绘制时间的估算结果,以及树木的视觉重要性,确定生成森林场景的最佳方案。该方法能够使复杂动态森林场景的生成时间保持较好的稳定性,并且在可视化过程中根据仿真效果动态调整绘制策略。为了验证该方法的有效性和实用性,在动态生长的森林仿真场景中对本文的方法进行了实验和应用。应用结果表明,多风格融合的森林场景自适应可视化方法能在保证森林场景可视化真实感的基础上,有效地提升复杂森林场景的绘制速度,使森林场景的快速漫游具有更好的稳定性和流畅性。     

View-dependent textured splatting

We present a novel approach to render low resolution point clouds with multiple high resolution textures – the type of data typical from passive vision systems. The low precision, noisy, and sometimes incomplete nature of such data sets is not suitable for existing point-based rendering techniques that are designed to work with high precision and high density point clouds. Our new algorithm – view-dependent textured splatting (VDTS) – combines traditional splatting with a view-dependent texturing strategy to reduce rendering artifacts caused by imprecision or noise in the input data.VDTS requires no pre-processing of input data, addresses texture aliasing, and most importantly, processes texture visibility on-the-fly. The combination of these characteristics makes VDTS well-suited for interactive rendering of dynamic scenes. Towards this end, we present a real-time view acquisition and rendering system to demonstrate the effectiveness of VDTS. In addition, we show that VDTS can produce high quality rendering when the texture images are augmented with per-pixel depth. In this scenario, VDTS is a reasonable alternative for interactive rendering of large CG models.     

A Survey of Surface‐Based Illustrative Rendering for Visualization

In this paper, we survey illustrative rendering techniques for 3D surface models. We first discuss the field of illustrative visualization in general and provide a new definition for this sub‐area of visualization. For the remainder of the survey, we then focus on surface‐based models. We start by briefly summarizing the differential geometry fundamental to many approaches and discuss additional general requirements for the underlying models and the methods' implementations. We then provide an overview of low‐level illustrative rendering techniques including sparse lines, stippling and hatching, and illustrative shading, connecting each of them to practical examples of visualization applications. We also mention evaluation approaches and list various application fields, before we close with a discussion of the state of the art and future work.     

Next Event Estimation++: Visibility Mapping for Efficient Light Transport Simulation

Monte-Carlo rendering requires determining the visibility between scene points as the most common and compute intense operation to establish paths between camera and light source. Unfortunately, many tests reveal occlusions and the corresponding paths do not contribute to the final image. In this work, we present next event estimation++ (NEE++): a visibility mapping technique to perform visibility tests in a more informed way by caching voxel to voxel visibility probabilities. We show two scenarios: Russian roulette style rejection of visibility tests and direct importance sampling of the visibility. We show applications to next event estimation and light sampling in a uni-directional path tracer, and light-subpath sampling in Bi-Directional Path Tracing. The technique is simple to implement, easy to add to existing rendering systems, and comes at almost no cost, as the required information can be directly extracted from the rendering process itself. It discards up to 80% of visibility tests on average, while reducing variance by ∼20% compared to other state-of-the-art light sampling techniques with the same number of samples. It gracefully handles complex scenes with efficiency similar to Metropolis light transport techniques but with a more uniform convergence.     

Direct interval volume visualization

We extend direct volume rendering with a unified model for generalized isosurfaces, also called interval volumes, allowing a wider spectrum of visual classification. We generalize the concept of scale-invariant opacity—typical for isosurface rendering—to semi-transparent interval volumes. Scale-invariant rendering is independent of physical space dimensions and therefore directly facilitates the analysis of data characteristics. Our model represents sharp isosurfaces as limits of interval volumes and combines them with features of direct volume rendering. Our objective is accurate rendering, guaranteeing that all isosurfaces and interval volumes are visualized in a crack-free way with correct spatial ordering. We achieve simultaneous direct and interval volume rendering by extending preintegration and explicit peak finding with data-driven splitting of ray integration and hybrid computation in physical and data domains. Our algorithm is suitable for efficient parallel processing for interactive applications as demonstrated by our CUDA implementation.     

Particle-based multiple irregular volume rendering on CUDA

In this paper, we describe an improved particle-based volume rendering (PBVR) technique for previewing a large irregular volume dataset using the CUDA architecture. This technique allows for opaque and emissive particles to render translucent volumes without visibility sorting. Our GPU acceleration of PBVR provides the multi-volume rendering feature while remaining compatible with both regular and irregular volumes. We also reduce the memory cost required for storing all sub-pixel values by proposing a pixel repetition technique for a large sub-pixel level. By adjusting the repetition level, we achieved a very smooth level of detail (LOD) control for trading quality for speed. Our work demonstrates a full-detail rendering rate from 5 to 10 fps for irregular volume data with mega-scale cell numbers on an NVIDIA GeForce 8800GTS.     

Thermodynamics of cosmological models with a variable matter equation of state

We consider cosmological models with a self-interacting scalar field and a perfect fluid with a variable equation of state in spatially flat Friedmann—Robertson—Walker space-times. The main purpose of the paper is a study of general thermodynamic properties of such models and their relationship with the dynamics of geometry.     

Punctuated simplification of man-made objects

We present a simplification algorithm for manifold polygonal meshes of plane-dominant models. Models of this type are likely to appear in man-made environments. While traditional simplification algorithms focus on generality and smooth meshes, the approach presented here considers a specific class of man-made models. By detecting and classifying edge loops on the mesh and providing a guided series of binary mesh partitions, our approach generates a series of simplified models, each of which better respects the semantics of these kinds of models than conventional approaches do. A guiding principle is to eliminate simplifications that do not make sense in constructed environments. This, coupled with the concept of “punctuated simplification”, leads to an approach that is both efficient and delivers high visual quality. Comparative results are given.     

Eigenvectors of directed graphs and importance scores: dominance,T-Rank,and sink remedies

We study the properties of the principal eigenvector for the adjacency matrix (and related matrices) for a general directed graph. In particular—motivated by the use of the eigenvector for estimating the “importance” of the nodes in the graph—we focus on the distribution of positive weight in this eigenvector, and give a coherent picture which builds upon and unites earlier results. We also propose a simple method—“T-Rank”—for generating importance scores. T-Rank generates authority scores via a one-level, non-normalized matrix, and is thus distinct from known methods such as PageRank (normalized), HITS (two-level), and SALSA (two-level and normalized). We show, using our understanding of the principal eigenvector, that T-Rank has a much less severe “sink problem” than does PageRank. Also, we offer numerical results which quantify the “tightly-knit community” or TKC effect. We find that T-Rank has a stronger TKC effect than PageRank, and we offer a novel interpolation method which allows for continuous tuning of the strength of this TKC effect. Finally, we propose two new “sink remedies”, i.e., methods for ensuring that the principal eigenvector is positive everywhere. One of our sink remedies (source pumping) is unique among sink remedies, in that it gives a positive eigenvector without rendering the graph strongly connected. We offer a preliminary evaluation of the effects and possible applications of these new sink remedies.     

Efficient visibility encoding for dynamic illumination in direct volume rendering

We present an algorithm that enables real-time dynamic shading in direct volume rendering using general lighting, including directional lights, point lights, and environment maps. Real-time performance is achieved by encoding local and global volumetric visibility using spherical harmonic (SH) basis functions stored in an efficient multiresolution grid over the extent of the volume. Our method enables high-frequency shadows in the spatial domain, but is limited to a low-frequency approximation of visibility and illumination in the angular domain. In a first pass, level of detail (LOD) selection in the grid is based on the current transfer function setting. This enables rapid online computation and SH projection of the local spherical distribution of visibility information. Using a piecewise integration of the SH coefficients over the local regions, the global visibility within the volume is then computed. By representing the light sources using their SH projections, the integral over lighting, visibility, and isotropic phase functions can be efficiently computed during rendering. The utility of our method is demonstrated in several examples showing the generality and interactive performance of the approach.     

Object-Space Visibility Ordering for Point-Based and Volume Rendering

This paper presents a method to accelerate algorithms that need a correct and complete visibility ordering of their data for rendering. The technique works by pre‐sorting primitives in object‐space using three lists (one for each axis: X, Y and Z), and then combining the lists using graphics hardware by rendering each list to a texture and merging the textures in the end. We validate our algorithm by applying it to the splatting technique using several types of rendering, including point‐based rendering and volume rendering. We also detail our hardware implementation for volume rendering using point sprites.     

Photon streaming for interactive global illumination in dynamic scenes

While many methods exist for simulating diffuse light inter-reflections, relatively few of them are adapted to dynamic scenes. Despite approximations made on the formal rendering equation, managing dynamic environments at interactive or real-time frame rates still remains one of the most challenging problems. This paper presents a lighting simulation system based on photon streaming, performed continuously on the central processor unit. The power corresponding to each photon impact is accumulated onto predefined points, called virtual light accumulators (or VLA). VLA are used during the rendering phase as virtual light sources. We also introduce a priority management system that automatically adapts to brutal changes during lighting simulation (for instance due to visibility changes or fast object motion). Our system naturally benefits from multi-core architecture. The rendering process is performed in real time using a graphics processor unit, independently from the lighting simulation process. As shown in the results, our method provides high framerates for dynamic scenes, with moving viewpoint, objects and light sources.     

Testing axioms for quantum theory on probabilistic toy-theories

In D’Ariano in Philosophy of Quantum Information and Entanglement, Cambridge University Press, Cambridge, UK (2010), one of the authors proposed a set of operational postulates to be considered for axiomatizing Quantum Theory. The underlying idea is to derive Quantum Theory as the mathematical representation of a fair operational framework, i.e. a set of rules which allows the experimenter to make predictions on future events on the basis of suitable tests, e.g. without interference from uncontrollable sources and having local control and low experimental complexity. In addition to causality, two main postulates have been considered: PFAITH (existence of a pure preparationally faithful state), and FAITHE (existence of a faithful effect). These postulates have exhibited an unexpected theoretical power, excluding all known nonquantum probabilistic theories. In the same paper also postulate PURIFY-1 (purifiability of all states) has been introduced, which later has been reconsidered in the stronger version PURIFY-2 (purifiability of all states unique up to reversible channels on the purifying system) in Chiribella et al. (Reversible realization of physical processes in probabilistic theories, arXiv:0908.1583). There, it has been shown that Postulate PURIFY-2, along with causality and local discriminability, narrow the probabilistic theory to something very close to the quantum one. In the present paper we test the above postulates on some nonquantum probabilistic models. The first model—the two-box world—is an extension of the Popescu–Rohrlich model (Found Phys, 24:379, 1994), which achieves the greatest violation of the CHSH inequality compatible with the no-signaling principle. The second model—the two-clock world— is actually a full class of models, all having a disk as convex set of states for the local system. One of them corresponds to—the two-rebit world— namely qubits with real Hilbert space. The third model—the spin-factor—is a sort of n-dimensional generalization of the clock. Finally the last model is the classical probabilistic theory. We see how each model violates some of the proposed postulates, when and how teleportation can be achieved, and we analyze other interesting connections between these postulate violations, along with deep relations between the local and the non-local structures of the probabilistic theory.     

Specification-oriented semantics for Communicating Processes

Summary A process P satisfies a specification S if every observation we can make of the behaviour of P is allowed by S. We use this idea of process correctness as a starting point for developing a specific form of denotational semantics for processes, called here specification — oriented semantics. This approach serves as a uniform framework for generating and relating a series of increasingly sophisticated denotational models for Communicating Processes. These models differ in the underlying structure of their observations which influences both the number of representable language operators and the induced notion of process correctness. Safety properties are treated by all models; the more sophisticated models also permit proofs of certain liveness properties. An important feature of the models is a special hiding operator which abstracts from internal process activity. This allows large processes to be composed hierarchically from networks of smaller ones in such a way that proofs of the whole are constructed from proofs of its components. We also show the consistency of our denotational models w.r.t. a simple operational semantics based on transitions which make internal process activity explicit. A preliminary version of this paper appeared in [42]     

Interactive Illustrative Rendering on Mobile Devices

Scientists, engineers, and artists regularly use illustrations in design, training, and education to display conceptual information, describe problems, and solve those problems. Researchers have developed many advanced rendering techniques on desktop platforms to facilitate illustration generation, but adapting these techniques to mobile platforms has not been easy. We discuss how advanced illustrative rendering techniques, such as interactive cutaway views, ghosted views, silhouettes, and selective rendering, have been adapted to mobile devices. We also present MobileVis, our interactive, illustrative 3D graphics and text rendering system that lets users explore 3D models' interior structures, display parts annotations, and visualize instructions, such as assembly and disassembly procedures for mechanical models     

Average Profile of the Lempel-Ziv Parsing Scheme for a Markovian Source

For a Markovian source, we analyze the Lempel—Ziv parsing scheme that partitions sequences into phrases such that a new phrase is the shortest phrase not seen in the past. We consider three models: In the Markov Independent model, several sequences are generated independently by Markovian sources, and the ith phrase is the shortest prefix of the ith sequence that was not seen before as a phrase (i.e., a prefix of previous (i-1) sequences). In the other two models, only a single sequence is generated by a Markovian source. In the second model, called the Gilbert—Kadota model, a fixed number of phrases is generated according to the Lempel—Ziv algorithm, thus producing a sequence of a variable (random) length. In the last model, known also as the Lempel—Ziv model, a string of fixed length is partitioned into a variable (random) number of phrases. These three models can be efficiently represented and analyzed by digital search trees that are of interest to other algorithms such as sorting, searching, and pattern matching. In this paper we concentrate on analyzing the average profile (i.e., the average number of phrases of a given length), the typical phrase length, and the length of the last phrase. We obtain asymptotic expansions for the mean and the variance of the phrase length, and we prove that appropriately normalized phrase length in all three models tends to the standard normal distribution, which leads to bounds on the average redundancy of the Lempel—Ziv code. For the Markov Independent model, this finding is established by analytic methods (i.e., generating functions, Mellin transform, and depoissonization), while for the other two models we use a combination of analytic and probabilistic analyses. Received June 6, 2000; revised January 14, 2001.     

Stochastic Soft Shadow Mapping

In this paper, we extend the concept of pre‐filtered shadow mapping to stochastic rasterization, enabling real‐time rendering of soft shadows from planar area lights. Most existing soft shadow mapping methods lose important visibility information by relying on pinhole renderings from an area light source, providing plausible results only for small light sources. Since we sample the entire 4D shadow light field stochastically, we are able to closely approximate shadows of large area lights as well. In order to efficiently reconstruct smooth shadows from this sparse data, we exploit the analogy of soft shadow computation to rendering defocus blur, and introduce a multiplane pre‐filtering algorithm. We demonstrate how existing pre‐filterable approximations of the visibility function, such as variance shadow mapping, can be extended to four dimensions within our framework.