Low power, long range, wireless communication technologies enable a range of monitoring applications in difficult to reach locations. In this paper, we investigate one such application for monitoring an underground pipeline infrastructure in the 868MHz Industrial, Scientific and Medical (ISM) band. We deployed five underground LoRa/LoRaWAN communication modules on district heating pipes, sealed off below an asphalted road segment. Several specific measurements have been conducted to characterize the propagation conditions from below to above ground, and from which we propose models decomposing propagation into separate contributions from soil, ground to free-space, and above ground propagation. The main novelty of the work lies in the application to covered surfaces and the combined above ground/aerial model framework for communication from below ground. It was found that the Peplinski soil loss model is applicable for estimating the effect of the ground, which in combination with Fresnel refraction and a log-distance model for above ground propagation leads to a consistent modeling framework for propagation to lamp post height gateway infrastructure. For aerial-based gateways, the main finding is that the propagation from below to above ground changes the propagation behavior with distance above ground, despite the otherwise unobstructed free space propagation path. This led to a path loss model with loss increasing exponentially with height and according to cylindrical wave propagation with lateral (2D) distance, aligning with the estimations based on the ground-based model. The results suggest overall that the volumetric water content (VWC) of a compacted and covered soil mixture tends to stabilize to high values.

Abstract We generalize N‐rooks, jittered, and (correlated) multi‐jittered sampling to higher dimensions by importing and improving upon a class of techniques called orthogonal arrays from the statistics literature. Renderers typically combine or “pad” a collection of lower‐dimensional (e.g. 2D and 1D) stratified patterns to form higher‐dimensional samples for integration. This maintains stratification in the original dimension pairs, but looses it for all other dimension pairs. For truly multi‐dimensional integrands like those in rendering, this increases variance and deteriorates its rate of convergence to that of pure random sampling. Care must therefore be taken to assign the primary dimension pairs to the dimensions with most integrand variation, but this complicates implementations. We tackle this problem by developing a collection of practical, in‐place multi‐dimensional sample generation routines that stratify points on all t‐dimensional and 1‐dimensional projections simultaneously . For instance, when t=2, any 2D projection of our samples is a (correlated) multi‐jittered point set. This property not only reduces variance, but also simplifies implementations since sample dimensions can now be assigned to integrand dimensions arbitrarily while maintaining the same level of stratification. Our techniques reduce variance compared to traditional 2D padding approaches like PBRT's (0,2) and Stratified samplers, and provide quality nearly equal to state‐of‐the‐art QMC samplers like Sobol and Halton while avoiding their structured artifacts as commonly seen when using a single sample set to cover an entire image. While in this work we focus on constructing finite sampling point sets, we also discuss potential avenues for extending our work to progressive sequences (more suitable for incremental rendering) in the future.

Abstract We introduce three new families of stochastic algorithms to generate progressive 2D sample point sequences. This opens a general framework that researchers and practitioners may find useful when developing future sample sequences. Our best sequences have the same low sampling error as the best known sequence (a particular randomization of the Sobol’ (0,2) sequence). The sample points are generated using a simple, diagonally alternating strategy that progressively fills in holes in increasingly fine stratifications. The sequences are progressive (hierarchical): any prefix is well distributed, making them suitable for incremental rendering and adaptive sampling. The first sample family is only jittered in 2D; we call it progressive jittered . It is nearly identical to existing sample sequences. The second family is multi‐jittered: the samples are stratified in both 1D and 2D; we call it progressive multi‐jittered . The third family is stratified in all elementary intervals in base 2, hence we call it progressive multi‐jittered (0,2) . We compare sampling error and convergence of our sequences with uniform random, best candidates, randomized quasi‐random sequences (Halton and Sobol'), Ahmed's ART sequences, and Perrier's LDBN sequences. We test the sequences on function integration and in two settings that are typical for computer graphics: pixel sampling and area light sampling. Within this new framework we present variations that generate visually pleasing samples with blue noise spectra, and well‐stratified interleaved multi‐class samples; we also suggest possible future variations.

Pixar’s RenderMan renderer is used to render all of Pixar’s films and by many film studios to render visual effects for live-action movies. RenderMan started as a scanline renderer based on the Reyes algorithm, and it was extended over the years with ray tracing and several global illumination algorithms. This article describes the modern version of RenderMan, a new architecture for an extensible and programmable path tracer with many features that are essential to handle the fiercely complex scenes in movie production. Users can write their own materials using a bxdf interface and their own light transport algorithms using an integrator interface—or they can use the materials and light transport algorithms provided with RenderMan. Complex geometry and textures are handled with efficient multi-resolution representations, with resolution chosen using path differentials. We trace rays and shade ray hit points in medium-sized groups, which provides the benefits of SIMD execution without excessive memory overhead or data streaming. The path-tracing architecture handles surface, subsurface, and volume scattering. We show examples of the use of path tracing, bidirectional path tracing, VCM, and UPBP light transport algorithms. We also describe our progressive rendering for interactive use and our adaptation of denoising techniques.

Abstract We present photon beam diffusion, an efficient numerical method for accurately rendering translucent materials. Our approach interprets incident light as a continuous beam of photons inside the material. Numerically integrating diffusion from such extended sources has long been assumed computationally prohibitive, leading to the ubiquitous single‐depth dipole approximation and the recent analytic sum‐of‐Gaussians approach employed by Quantized Diffusion. In this paper, we show that numerical integration of the extended beam is not only feasible, but provides increased speed, flexibility, numerical stability, and ease of implementation, while retaining the benefits of previous approaches. We leverage the improved diffusion model, but propose an efficient and numerically stable Monte Carlo integration scheme that gives equivalent results using only 3–5 samples instead of 20–60 Gaussians as in previous work. Our method can account for finite and multi‐layer materials, and additionally supports directional incident effects at surfaces. We also propose a novel diffuse exact single‐scattering term which can be integrated in tandem with the multi‐scattering approximation. Our numerical approach furthermore allows us to easily correct inaccuracies of the diffusion model and even combine it with more general Monte Carlo rendering algorithms. We provide practical details necessary for efficient implementation, and demonstrate the versatility of our technique by incorporating it on top of several rendering algorithms in both research and production rendering systems.

Abstract When rendering only directly visible objects, ray tracing a few levels of specular reflection from large, low‐curvaturesurfaces, and ray tracing shadows from point‐like light sources, the accessed geometry is coherentand a geometry cache performs well. But in many other cases, the accessed geometry is incoherent and a standardgeometry cache performs poorly: ray tracing of specular reflection from highly curved surfaces, tracing rays thatare many reflection levels deep, and distribution ray tracing for wide glossy reflection, global illumination, widesoft shadows, and ambient occlusion. Fortunately, less geometric accuracy is necessary in the incoherent cases.This observation can be formalized by looking at the ray differentials for different types of scattering: coherentrays have small differentials, while incoherent rays have large differentials. We utilize this observation to obtainefficient multiresolution caching of geometry and textures (including displacement maps) for classic and distributionray tracing in complex scenes. We use an existing multiresolution caching scheme (originally developed forscanline rendering) for textures and displacement maps, and introduce a multiresolution geometry caching schemefor tessellated surfaces. The multiresolution geometry caching scheme makes it possible to efficiently render scenesthat, if fully tessellated, would use 100 times more memory than the geometry cache size.

This survey gives an overview of the use of importance, an adjoint of light, in speeding up rendering. The importance of a light distribution indicates its contribution to the region of most interest-typically the directly visible parts of a scene. Importance can therefore be used to concentrate global illumination and ray tracing calculations where they matter most for image accuracy, while reducing computations in areas of the scene that do not significantly influence the image. In this paper, we attempt to clarify the various uses of adjoints and importance in rendering by unifying them into a single framework. While doing so, we also generalize some theoretical results-known from discrete representations-to a continuous domain.

Article Efficient simulation of light transport in scenes with participating media using photon maps Share on Authors: Henrik Wann Jensen mental images, Berlin, Germany mental images, Berlin, GermanyView Profile , Per H. Christensen mental images, Berlin, Germany mental images, Berlin, GermanyView Profile Authors Info & Claims SIGGRAPH '98: Proceedings of the 25th annual conference on Computer graphics and interactive techniquesJuly 1998 Pages 311–320https://doi.org/10.1145/280814.280925Online:24 July 1998Publication History 245citation5,023DownloadsMetricsTotal Citations245Total Downloads5,023Last 12 Months92Last 6 weeks12 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

We present a new clustering algorithm for global illumination in complex environments. The new algorithm extends provious work on clustering for radiosity to allow for nondiffuse (glossy) reflectors. We represent clusters as points with directional distributions of outgoing and incoming radiance and importance, and we derive an error bound for transfers between these clusters. The algorithm groups input surfaces into a hierarchy of clusters, and then permits clusters to interact only if the error bound is below an acceptable tolerance. We show that the algorithm is asymptotically more efficient than previous clustering algorithms even when restricted to ideally diffuse environments. Finally, we demonstrate the performance of our method on two complex glossy environments.

We show how importance-driven refinement and a wavelet basis can be combined to provide an efficient solution to the global illumination problem with glossy and diffuse reflections. Importance is used to focus the computation on the interactions having the greatest impact on the visible solution. Wavelets are used to provide an efficient representation of radiance, importance, and the transport operator. We discuss a number of choices that must be made when constructing a finite element algorithm for glossy global illumination. Our algorithm is based on the standard wavelet decomposition of the transport operator and makes use of a four-dimensional wavelet representation for spatially and angularly varying radiance distributions. We use a final gathering step to improve the visual quality of the solution. Features of our implementation include support for curved surfaces as well as texture-mapped anisotropic emission and reflection functions.

The utilization of color information to increase the accuracy of 3-D shapes derived from photometric stereo is described. Multicolored objects under white illumination are considered. Using color images rather than gray-scale makes it simple to separate the specular and diffuse reflection components. The diverse properties of diffusive and specular reflection yield supplementing constraints on the surface orientation, making the method less sensitive to noise.>