Shadow Map Research Articles

Geographical variation in energy yields of rooftop photovoltaic projects in Australia

ABSTRACTPrecise estimation of rooftop-received solar energy is essential for the efficient energy generation of photovoltaic (PV) projects and the development of energy policies. Conventional measurements usually adopt light detection and ranging (LIDAR) data, which can only be extracted from existing buildings, to estimate the solar radiation potential of building rooftops in a region. This research establishes a pixel-based estimation method for investigating the effects of different geolocations on energy output and yield distributions of rooftop PV systems by formulating estimation equations for the SketchUp platform. Based on the proposed alorighm, the solar radiation on a certain cell of a shadow map is mathematically formulated for each pixel unit. A building model derived from a typical Australian house with flat and pitched roofs is then chosen as a case study in this paper. The potential electrical energy from the rooftop PV systems is then measured and analysed considering solar radiation potentials in different geographical positions. This study will benefit commercial and individual energy investors in the efficient use of renewable energy sources through the accurate prediction of radiation-based energy yields and the identification of areas that can provide high energy revenues on building roofs for different geolocations.

Fast Ray-Scene Intersection for Interactive Shadow Rendering with Thousands of Dynamic Lights.

We present a method for the fast computation of the intersection between a ray and the geometry of a scene. The scene geometry is simplified with a 2D array of voxelizations computed from different directions, sampling the space of all possible directions. The 2D array of voxelizations is compressed using a vector quantization approach. The ray-scene intersection is approximated using the voxelization whose rows are most closely aligned with the ray. The voxelization row that contains the ray is looked up, the row is truncated to the extent of the ray using bit operations, and a truncated row with non-zero bits indicates that the ray intersects the scene. We support dynamic scenes with rigidly moving objects by building a separate 2D array of voxelizations for each type of object, and by using the same 2D array of voxelizations for all instances of an object type. We support complex dynamic scenes and scenes with deforming geometry by computing and rotating a single voxelization on the fly. We demonstrate the benefits of our method in the context of interactive rendering of scenes with thousands of moving lights, where we compare our method to ray tracing, to conventional shadow mapping, and to imperfect shadow maps.

Shadow Accrual Maps: Efficient Accumulation of City-Scale Shadows Over Time.

Large scale shadows from buildings in a city play an important role in determining the environmental quality of public spaces. They can be both beneficial, such as for pedestrians during summer, and detrimental, by impacting vegetation and by blocking direct sunlight. Determining the effects of shadows requires the accumulation of shadows over time across different periods in a year. In this paper, we propose a simple yet efficient class of approach that uses the properties of sun movement to track the changing position of shadows within a fixed time interval. We use this approach to extend two commonly used shadow techniques, shadow maps and ray tracing, and demonstrate the efficiency of our approach. Our technique is used to develop an interactive visual analysis system, Shadow Profiler, targeted at city planners and architects that allows them to test the impact of shadows for different development scenarios. We validate the usefulness of this system through case studies set in Manhattan, a dense borough of New York City.

Deshadowing of Urban Airborne Imagery Based on Object-Oriented Automatic Shadow Detection and Regional Matching Compensation

With the increase of the spatial resolution of aerial images, the shadow problem is more prominent. The shadows affect the applications such as object recognition, image dense matching, and object classification. Existing shadow detection methods can acquire results with high accuracy, but usually need much manual intervention and the traditional stretch models generally lead to color distortion and undercompensation. Therefore, we propose an object-oriented automatic shadow detection method without manual intervention and a shadow compensation method by regional matching. In the proposed method, pixel-based soft shadow detection, which uses Gaussian mixture model to simulate the gray distribution and refines soft shadow map with guiled filtering, is combined with image segmentation result to obtain accurate shadow regions with complete shape and no hole. Then shadow regions are compensated, with less loss of details and brightness imbalance, referring to their optimal homogeneous nonshadow region obtained by regional matching based on Bag-of-Words. The total variation model is used to decrease the noise amplified by the pixel-based stretch and boundary effect in the result. Experiments are performed on three publicly available high-resolution aerial images to demonstrate the superiority of our proposed methods. It shows that the proposed method can accurately detect shadows from urban high-resolution aerial images with an overall rate of over 88%. The compensation results display excellent visual effects compared with the state-of-the-art methods, consistent with the true color of ground objects.

Cast Shadow Detection to Quantify the Aerosol Optical Thickness for Atmospheric Correction of High Spatial Resolution Optical Imagery

The atmospheric correction of optical remote sensing data requires the determination of aerosol and gas optical properties. A method is presented which allows the detection of the aerosol scattering effects from optical remote sensing data at spatial sampling intervals below 5 m in cloud-free situations from cast shadow pixels. The derived aerosol optical thickness distribution is used for improved atmospheric compensation. In a first step, a novel spectral cast shadow detection algorithm determines the shadow areas using spectral indices. Evaluation of the cast shadow masks shows an overall classification accuracy on an 80% level. Using the such derived shadow map, the ATCOR atmospheric compensation method is iteratively applied on the shadow areas in order to find the optimum aerosol amount. The aerosol optical thickness is found by analyzing the physical atmospheric correction of fully shaded pixels in comparison to directly illuminated areas. The shadow based aerosol optical thickness estimation method (SHAOT) is tested on airborne imaging spectroscopy data as well as on photogrammetric data. The accuracy of the reflectance values from atmospheric correction using the such derived aerosol optical thickness could be improved from 3–4% to a level of better than 2% in reflectance for the investigated test cases.

A Brutal Reality

A Brutal Reality Christopher Higgs (bio) A Shadow Map: An Anthology of Survivors of Sexual Assault Joanna C. Valente, ed. Civil Coping Mechanisms www.copingmechanisms.net/portfolio 364 Pages; Print, $15.95 Nothing could have prepared me for the overwhelming intensity of the writing in this powerful collection of over fifty diverse writers on the topic of surviving sexual assault. In an interview with Vol. 1 Brooklyn, editor Joanna C. Valente, a New York based poet whose work often grapples with issues surrounding violence and its aftermath, described the project as, “[S]ome of the most important work I’ll ever do. Being able to create a safe space, a space where survivors could share their stories and fight stigma and raise awareness not only on what sexual assault is, but how the aftermath stays with you forever, was paramount to me as a survivor myself.” Indeed, from the opening cluster of three previously published poems by Lynn Melnick—with the lines, “At night I hallucinate the grunting discord / which leapt from a human body as he destroyed mine”—which sets the tone by thrusting the horror of rape directly in the reader’s face, to the final piece by Corinne Manning where she writes, “To heal is to bring into words what once existed as non-verbal,” A Shadow Map never flinches, never backs away, never shies away, never defers. Women get raped repeatedly. Men, too. Trans and nonbinary people, too. And children, so many children raped and left to deal with the aftermath. Incest, pedophilia, torture. It’s brutal and gruesome and unspeakable, but yet, as Manning says, we must bring the unspeakable into the speakable if healing can ever occur. Because these are real people with real stories and our job as the reader must include listening to and believing them. That said, the overall reading experience for me recalled that memorably uncomfortable scene in Stanley Kubrick’s film adaptation of A Clockwork Orange (1972) where the main character is subjected to an aversion therapy tactic called the Ludovico Technique, whereby he’s forced to watch violent images for extended periods of time while his eyes are held open with specula. In fact, I found myself reading a page or two and then hastily putting it down and grasping for something else, anything else, to occupy my attention in order to try and flush the images from my mind, to escape the reality the text presented me. After reading the opening pages I quite honestly did not want to continue reading this book. I did not want to inhabit this world, did not want to confront these true stories of sexual violence and trauma, and instead I wanted to retreat into the privilege of my own experience devoid of sexual harassment and assault. I wanted to look away and pretend these things don’t happen or if they did I wanted to ignore them and presume they happen only rarely and thankfully not to me. And I write this not as a prude, for so easily I confront these issues in fictive narratives: I routinely teach brutal books by Kathy Acker and William Burroughs and Pierre Guyotat, disturbing films by Takashi Miike and Gaspar Noe and other torture porn auteurs, without a blink of the eye. However, the nonfictive quality of the material in this collection demands a different type of engagement. Again I feel compelled to say these writers are real people, not functions of an imagination. Real people who suffered real trauma. For me, this realization made it nearly intolerable to read. I have a four year old son, and all I could think about while reading this text was that although I had somehow made it to my forties without suffering in the ways these writers suffered, he could so easily become a victim. And obviously each of these writers is someone’s child. Even trying to compose this response to the book right now, I’m having a hard time holding back tears. I share my personal thoughts with you to demonstrate the supremely personal power of this text. I could’ve easily taken a more...

Improved anti-aliasing for Euclidean distance transform shadow mapping

High-quality, real-time penumbra rendering remains a challenging problem in computer graphics. Existing techniques for real-time fixed-size penumbra simulation generate aliasing, banding or leaking artifacts that diminish the realism of shadow rendering. Euclidean distance transform shadow mapping aims to solve that by using a normalized Euclidean distance transform to simulate penumbra on the basis of anti-aliased hard shadows generated by revectorization-based shadow mapping. Despite the high visual quality obtained with such a technique, the anti-aliasing provided by shadow revectorization comes at the cost of shadow overestimation artifacts that are introduced in the scene. In this paper, we propose an improved algorithm for Euclidean distance transform shadow mapping by reformulating the visibility function of revectorization-based shadow mapping. Through an additional detailed analysis of the results, we show that we are able to reduce shadow overestimation artifacts for penumbra simulation, generating shadows with higher visual quality than previous fixed-size penumbra shadowing methods, while keeping real-time performance for shadow rendering.

Efficient motion blurred shadows using a temporal shadow map

In this paper, we propose a novel algorithm that renders motion blurred shadows efficiently on GPUs using a temporal shadow map. Each triangle moves during a frame and for each pixel, it is visible...

Realistic real-time rendering of light shafts using blur filter: considering the effect of shadow maps

The ray marching method has become the most attractive method to provide realism in rendering the effects of light scattering in the participating media of numerous applications. This has attracted significant attention from scientific community. Up-sampling of ray marching method is suitable for rendering light shafts of realistic scenes, but suffers of consume a lot of time for rendering. Therefore, some encouraging outcomes have been achieved by using down-sampling of ray marching approach to accelerate rendered scenes. However, these methods are inherently prone to artifacts, aliasing and incorrect boundaries due to the reduced number of sample points along view rays. This research proposes a realistic real-time technique to generate soft light shafts by making use downsampling of ray marching in generating light shafts. The bilateral filtering is then applied to overcome all defects that caused by downsampling process to make a scene with smoothing transition while preserving on the edges. The contribution of this technique is to improve the boundaries of light shafts taking into account the effect of shadows. This technique allows obtaining soft marvelous light shafts, having a good performance and high quality. Thus, it is suitable for interactive applications.

Intermediate shadow maps for interactive many-light rendering

We present an efficient method for computing shadows for many light sources (e.g., 1024). Our work is based on the observation that conventional shadow mapping becomes redundant as the number of lights increases. First, we sample the scene with a constant number of depth images (e.g., 10), which we call intermediate shadow maps. Then the shadow map for each light is approximated by rendering triangles reconstructed from the intermediate shadow maps. The cost of rendering these triangles is much smaller than rendering the original geometry of a complex scene. The algorithm supports fully dynamic scenes. Our results show that our method can produce soft shadows comparable to those obtained by conventional shadow mapping for each light source or by ray tracing, but at a higher frame rate.

Real-Time Cloth Rendering with Fiber-Level Detail.

Modeling cloth with fiber-level geometry can produce highly realistic details. However, rendering fiber-level cloth models not only has a high memory cost but it also has a high computation cost even for offline rendering applications. In this paper we present a real-time fiber-level cloth rendering method for current GPUs. Our method procedurally generates fiber-level geometric details on-the-fly using yarn-level control points for minimizing the data transfer to the GPU. We also reduce the rasterization operations by collectively representing the fibers near the center of each ply that form the yarn structure. Moreover, we employ a level-of-detail strategy to minimize or completely eliminate the generation of fiber-level geometry that would have little or no impact on the final rendered image. Furthermore, we introduce a simple self-shadow computation method that allows lighting with self-shadows using relatively low-resolution shadow maps. We also provide a simple distance-based ambient occlusion approximation as well as an ambient illumination precomputation approach, both of which account for fiber-level self-occlusion of yarn. Finally, we discuss how to use a physical-based shading model with our fiber-level cloth rendering method and how to handle cloth animations with temporal coherency. We demonstrate the effectiveness of our approach by comparing our simplified fiber geometry to procedurally generated references and display knitwear containing more than a hundred million individual fiber curves at real-time frame rates with shadows and ambient occlusion.

Efficient motion blurred shadows using a temporal shadow map

In this paper, we propose a novel algorithm that renders motion blurred shadows efficiently on GPUs using a temporal shadow map. Each triangle moves during a frame and for each pixel, it is visible to the light in a range of time. The main idea of our algorithm is to find such visible ranges and store in the temporal shadow map. For each sample which is visible to the camera at a certain time, we can determine whether it is shadowed or lit using visible ranges in the temporal shadow map. Thus, our algorithm solves a time-mismatch problem in the time-dependent shadow mapping algorithm. Furthermore, we use a coverage map to reduce memory footprint used for the temporal shadow map.

Soft bilateral filtering volumetric shadows using cube shadow maps.

Volumetric shadows often increase the realism of rendered scenes in computer graphics. Typical volumetric shadows techniques do not provide a smooth transition effect in real-time with conservation on crispness of boundaries. This research presents a new technique for generating high quality volumetric shadows by sampling and interpolation. Contrary to conventional ray marching method, which requires extensive time, this proposed technique adopts downsampling in calculating ray marching. Furthermore, light scattering is computed in High Dynamic Range buffer to generate tone mapping. The bilateral interpolation is used along a view rays to smooth transition of volumetric shadows with respect to preserving-edges. In addition, this technique applied a cube shadow map to create multiple shadows. The contribution of this technique isreducing the number of sample points in evaluating light scattering and then introducing bilateral interpolation to improve volumetric shadows. This contribution is done by removing the inherent deficiencies significantly in shadow maps. This technique allows obtaining soft marvelous volumetric shadows, having a good performance and high quality, which show its potential for interactive applications.

Spatial Adjacency Maps for Translucency Simulation under General Illumination

Rendering translucent materials in real time is usually done by using surface diffusion and/or translucent shadow maps. The downsides of these approaches are, that surface diffusion cannot handle translucency effects that show up when rendering thin objects, and that translucent shadow maps are only available for point light sources. Furthermore, translucent shadow maps introduce limitations to shadow mapping techniques exploiting the same maps. In this paper we present a novel approach for rendering translucent materials at interactive frame rates. Our approach allows for an efficient calculation of translucency with native support for general illumination conditions, especially area and environment lighting, at high accuracy. The proposed technique's only parameter is the used diffusion profile, and thus it works out of the box without any parameter tuning. Furthermore, it can be used in combination with any existing surface diffusion techniques to add translucency effects. Our approach introduces Spatial Adjacency Maps that depend on precalculations to be done for fixed meshes. We show that these maps can be updated in real time to also handle deforming meshes and that our results are of superior quality as compared to other well known real-time techniques for rendering translucency.

Automatic Detection of Game Engine Artifacts Using Full Reference Image Quality Metrics

Contemporary game engines offer an outstanding graphics quality but they are not free from visual artifacts. A typical example is aliasing, which, despite advanced antialiasing techniques, is still visible to the game players. Essential deteriorations are the shadow acne and peter panning responsible for deficiency of the shadow mapping technique. Also Z-fighting, caused by the incorrect order of drawing polygons, significantly affects the quality of the graphics and makes the gameplay more difficult. In this work, we propose a technique, in which visibility of deteriorations is uncovered by the objective image quality metrics (IQMs). We test the efficiency of a simple mathematically based metric and advanced IQMs: a Spatial extension of CIELAB (S-CIELAB), the Structural SIMilarity Index (SSIM), the Multiscale Structural SIMilarity Index (MS-SSIM), and the High Dynamic Range Visual Difference Predictor-2 (HDR-VDP-2). Additionally, we evaluate the Color Image Difference (CID) metric, which is recommended to detect the differences in colors. To find out which metric is the most effective for the detection of the game engine artifacts, we build a database of manually marked images with representative set of artifacts. We conduct subjective experiments in which people manually mark the visible local artifacts in the screenshots from the games. Then the detection maps averaged over a number of observers are compared with results generated by IQMs. The obtained results show that SSIM and MS-SSIM metrics outperform other techniques. However, the results are not indisputable, because, for small and scattered aliasing artifacts, HDR-VDP-2 metrics report the results most consistent with the average human observer. As a proof of concept, we propose an application in which resolution of the shadow maps is controlled by the SSIM metric to avoid perceptually visible aliasing artifacts on the shadow edges.

Coregistration of Satellite Images and Airborne LiDAR Data Through the Automatic Bias Reduction of RPCs

Rational polynomial coefficients (RPCs), which are provided for most of the commercial satellite images, match relevant image locations to their three-dimensional-ground positions. In spite of their key role in most of remote sensing analysis, a considerable amount of bias is usually seen in the RPCs that necessitate their refinement as a common preprocessing. This refinement is typically performed using some complimentary control information (e.g., ground control points). This paper proposes a matching scheme between the georeferenced airborne LiDAR data and high-resolution satellite images (HRSI) to automatically obtain the control data that is required for RPCs bias compensation. The main contribution of this paper is the design and implementation of a shadow-based matching strategy to correspond the inherently different HRSI and LiDAR data. In this process, RPCs are regarded as the initial relating model between HRSI and LiDAR data and the existing bias of these parameters are ultimately reduced. A novel method, called incremental clustering, is used to automatically detect the shadow cast from the HRSI. In addition, a geometrical method is developed for shadow reconstructions from LiDAR data. These generated shadow maps are then assimilated from geometrical point of view as well as coordinate systems. Finally, a frequency domain matching is performed to find and compensate for the existent bias in RPCs. The obtained results indicate a precise bias reduction of the RPCs, where the initial misalignment of georeferencing is improved from 18 m (30 pixels) to about 0.58 m (1 pixel).

Estimating solar energy potentials on pitched roofs

Pitched-roof buildings make up a considerable proportion of architectural roof styles. Precise estimation of solar energy potential on pitched roofs is thus crucial to the sustainable development and renewable energy consumption of human habitats. Conventional solar radiation measurements usually adopt Light Detection and Ranging (LiDAR) data, which can only be extracted from existing buildings. There has been relatively little research assessing solar radiation on pitched roofs. This paper develops a pixel-based approach to estimation of solar energy potentials over pitched roofs based on the pretext of architectural design drawings. A typical Australian house with nine roofs is then chosen for implementation through a case study. The solar radiation on a certain cell of a shadow map is mathematically formulated for each pixel unit. Its yields over a certain time period are calculated by considering multiple instantaneous solar irradiances and visually presented through image processing. The resulting solar radiation maps, especially a coloured 3D map, reveal the roofs’ radiation distribution including effects from objects on the roofs such as chimneys. Radiation contour lines are mapped to obtain installation ranges for solar devices. This study will benefit commercial energy investors, residents and urban planners in the efficient use of renewable energy sources through accurate prediction of solar radiation potential and identification of areas receiving high radiation over sloping roofs.

An Efficient Soft Shadow Mapping for Area Lights in Various Shapes and Colors

An Efficient Soft Shadow Mapping for Area Lights in Various Shapes and Colors

Merged Multiresolution Hierarchies for Shadow Map Compression

AbstractMultiresolution Hierarchies (MH) and Directed Acyclic Graphs (DAG) are two recent approaches for the compression of high‐resolution shadow information. In this paper, we introduce Merged Multiresolution Hierarchies (MMH), a novel data structure that unifies both concepts. An MMH leverages both hierarchical homogeneity exploited in MHs, as well as topological similarities exploited in DAG representations. We propose an efficient hash‐based technique to quickly identify and remove redundant subtree instances in a modified relative MH representation. Our solution remains lossless and significantly improves the compression rate compared to both preceding shadow map compression algorithms, while retaining the full run‐time performance of traditional MH representations.

Shadow-Based Hierarchical Matching for the Automatic Registration of Airborne LiDAR Data and Space Imagery

The automatic registration of LiDAR data and optical images, which are heterogeneous data sources, has been a major research challenge in recent years. In this paper, a novel hierarchical method is proposed in which the least amount of interaction of a skilled operator is required. Thereby, two shadow extraction schemes, one from LiDAR and the other from high-resolution satellite images, were used, and the obtained 2D shadow maps were then considered as prospective matching entities. Taken as the base, the reconstructed LiDAR shadows were transformed to image shadows using a four-step hierarchical method starting from a coarse 2D registration model and leading to a fine 3D registration model. In the first step, a general matching was performed in the frequency domain that yielded a rough 2D similarity model that related the LiDAR and image shadow masks. This model was further improved by modeling and compensating for the local geometric distortions that existed between the two heterogeneous data sources. In the third step, shadow masks, which were organized as segmented matched patches, were the subjects of a coinciding procedure that resulted in a coarse 3D registration model. In the last hierarchical step, that model was ultimately reinforced via a precise matching between the LiDAR and image edges. The evaluation results, which were conducted on six datasets and from different relative and absolute aspects, demonstrated the efficiency of the proposed method, which had a very promising accuracy on the order of one pixel.