Graphics Hardware Research Articles

Gradient Estimation for Real-time Adaptive Temporal Filtering

With the push towards physically based rendering, stochastic sampling of shading, e.g. using path tracing, is becoming increasingly important in real-time rendering. To achieve high performance, only low sample counts are viable, which necessitates the use of sophisticated reconstruction filters. Recent research on such filters has shown dramatic improvements in both quality and performance. They exploit the coherence of consecutive frames by reusing temporal information to achieve stable, denoised results. However, existing temporal filters often create objectionable artifacts such as ghosting and lag. We propose a novel temporal filter which analyzes the signal over time to derive adaptive temporal accumulation factors per pixel. It repurposes a subset of the shading budget to sparsely sample and reconstruct the temporal gradient. This allows us to reliably detect sudden changes of the sampled signal and to drop stale history information. We create gradient samples through forward-projection of surface samples from the previous frame into the current frame and by reevaluating the shading samples using the same random sequence. We apply our filter to improve real-time path tracers. Compared to previous work, we show a significant reduction of lag and ghosting as well as improved temporal stability. Our temporal filter runs in 2 ms at 1080p on modern graphics hardware and can be integrated into deferred renderers.

View-Region Optimized Image-Based Scene Simplification

We present a new algorithm for image-based simplification of complex scenes for virtual reality (VR). The algorithm transforms geometrically-detailed environments into a layered quad tile representation that is optimized for a specified viewing region and is renderable on low-power mobile-class VR devices. A novel constrained optimization formulation ensures that the scene can be rendered within a predetermined compute budget, with limits on both primitive count and fill rate. Furthermore, we introduce a new method for texturing from point samples of the original scene geometry that generates high-quality silhouettes without the drawbacks of traditional point splatting. The resulting representation achieves a visual fidelity that was previously impossible on mobile graphics hardware; our algorithm can typically generate a high-quality representation of visually-rich scenes with billions of triangles using just 72k triangles and a single high-resolution texture map (with generally only about 50% more texels than a stereo panorama). The effectiveness of the approach is demonstrated with a set of challenging test cases.

On-the-fly Vertex Reuse for Massively-Parallel Software Geometry Processing

Due to its flexibility, compute mode is becoming more and more attractive as a way to implement many of the algorithms part of a state-of-the-art rendering pipeline. A key problem commonly encountered in graphics applications is streaming vertex and geometry processing. In a typical triangle mesh, the same vertex is on average referenced six times. To avoid redundant computation during rendering, a post-transform cache is traditionally employed to reuse vertex processing results. However, such a vertex cache can generally not be implemented efficiently in software and does not scale well as parallelism increases. We explore alternative strategies for reusing per-vertex results on-the-fly during massively-parallel software geometry processing. Given an input stream divided into batches, we analyze the effectiveness of sorting, hashing, and intra-thread-group communication for identifying and exploiting local reuse potential. We design and present four vertex reuse strategies tailored to modern GPU architectures. We demonstrate that, in a variety of applications, these strategies not only achieve effective reuse of vertex processing results, but can boost performance by up to 2-3x compared to a naïve approach. Curiously, our experiments also show that our batch-based approaches exhibit behavior similar to the OpenGL implementation on current graphics hardware.

Simulation of water surface using current consumer-level graphics hardware

Water surface visualization is an important research topic in computer graphics. This paper presents a novel method of water surface simulation by Secondary Distorted Textures (SDT), which realistically simulates and visualizes the reflection and refraction of calm water in real-time using current consumer-level hardware. The proposed method renders water surface using two stages of texture maps. 1. The first texture map stores the 3D geometries’ perspective reflection with respect to 3D perspective view; 2. The second texture map stores the distortion results of the first reflection map with lighting effects. Perlin noise is used to generate random height map. Reflection and refraction are obtained and stored in the secondary distorted texture map with Fresnel effects for each frame. At rendering pass, the SDT is directly tiled on water surface. This paper also discussed the rendering of transparent geometry, which have view-dependent of lighting effects features. Experimental results demonstrated that our method can render realistic geometry nearby dynamic water surface at the frame rates of 70-100 FPS by NVIDIA Quadro k5000 graphic card. The existing texture mapping and bump mapping methods were compared for illustrating that our method produced high realistic water surface without aliasing reflection.

A high-performance software graphics pipeline architecture for the GPU

In this paper, we present a real-time graphics pipeline implemented entirely in software on a modern GPU. As opposed to previous work, our approach features a fully-concurrent, multi-stage, streaming design with dynamic load balancing, capable of operating efficiently within bounded memory. We address issues such as primitive order, vertex reuse, and screen-space derivatives of dependent variables, which are essential to real-world applications, but have largely been ignored by comparable work in the past. The power of a software approach lies in the ability to tailor the graphics pipeline to any given application. In exploration of this potential, we design and implement four novel pipeline modifications. Evaluation of the performance of our approach on more than 100 real-world scenes collected from video games shows rendering speeds within one order of magnitude of the hardware graphics pipeline as well as significant improvements over previous work, not only in terms of capabilities and performance, but also robustness.

Real-Time Continuous Image Processing

In this work, we propose a framework that performs a number of popular image-processing operations in the continuous domain. This is in contrast to the standard practice of defining them as operations over discrete sequences of sampled values. The guiding principle is that, in order to prevent aliasing, nonlinear image-processing operations should ideally be performed prior to prefiltering and sampling. This is of course impractical, as we may not have access to the continuous input. Even so, we show that it is best to apply image-processing operations over the continuous reconstruction of the input. This transformed continuous representation is then prefiltered and sampled to produce the output. The use of high-quality reconstruction strategies brings this alternative much closer to the ideal than directly operating over discrete values. We illustrate the advantages of our framework with several popular effects. In each case, we demonstrate the quality difference between continuous image-processing, their discrete counterparts and previous anti-aliasing alternatives. Finally, our GPU implementation shows that current graphics hardware has enough computational power to perform continuous image processing in real-time.

Localization of 3D objects using model-constrained SLAM

Accurate and real-time camera localization relative to an object is needed for high-quality Augmented Reality applications. However, static object tracking is not an easy task in an industrial context where objects may be textured or not, have sharp edges or occluding contours, be relatively small or too large to be entirely observable from one point of view. This paper presents a localization solution built on a keyframe-based SLAM algorithm. This solution only requires a video stream of a 2D camera (color or grayscale) and the prior knowledge of a 3D mesh model of the object to localize (also named object of interest in this document). The 3D model provides an absolute constraint that drastically reduces the SLAM drift. It is based on 3D-oriented contour points called edgelets, dynamically extracted from the model using Analysis-by-Synthesis on the graphics hardware. This model constraint is then expressed through two different formalisms in the SLAM optimization process. The dynamic edgelet generation ensures the genericity of our tracking method, since it allows to localize polyhedral and curved objects. The proposed solution is easy to deploy, requiring no manual intervention on the model, and runs in real time on HD video streams. It is thus perfectly adapted for high-quality Augmented Reality experiences. Videos are available as supplementary material.

Has autism found a place in mainstream TV?

Has autism found a place in mainstream TV?

Effects of compaction pressure on the temperature distribution in bunker type silage silo

The aim of the research has been to determine effects of compaction pressureon temperature distribution in the silage material in bunker silo.The pressure measurement systemdeveloped within the scope of this research was used to measure the pressure distribution in the silo. Hobo E-348-UA-002–08 model temperature sensors were also used for temperature measurements.The all sensors were positioned in the silo at predetermined points. Temperature and pressure values were recorded in a datalogger during ensiling, fermentation and after fermentation stages.The data collection system is based on a graphical programming language NI LabVIEW software and NI CompactDAQ hardware modules.Work machine having palette of which weight was 13700 kg has been used to compact of maize silage.The average temperature of silage in the silo was 23.35 °C during ensiling, 29.04 °C during fermentation and 23.45 °Cduring the after fermentation stage.The maximum pressure on the silage material was applied during storage with a mean value of 0.34 bar. The highest temperature and pressure wereon the line in thefront of the silo while the lowest temperature and pressure were in the close to the rear wall of the silo.The effect of compaction pressure applied during the ensiling stage also continued during the fermentation stage.It was determined that there is a relationship between the pressure applied to silage and temperature. Results showed that temperature in the silage has been increased with increasing compaction pressure.

Variational approach for capsule video frame interpolation

Capsule video endoscopy, which uses a wireless camera to visualize the digestive tract, is emerging as an alternative to traditional colonoscopy. Colonoscopy is considered as the gold standard for visualizing the colon and takes 30 frames per second. Capsule images, on the other hand, are taken with low frame rate (average five frames per second), which makes it difficult to find pathology and results in eye fatigue for viewing. In this paper, we propose a variational algorithm to smooth the video temporally and create a visually pleasant video. The main objective of the paper is to increase the frame rate to be closer to that of the colonoscopy. We propose variational energy that takes into consideration both motion estimation and intermediate frame intensity interpolation using the surrounding frames. The proposed formulation incorporates both pixel intensity and texture feature in the optical flow objective function such that the interpolation at the intermediate frame is directly modeled. The main feature of this formulation is that error in motion estimation is incorporated in our model, so that only robust motion estimation are used in estimating the intensity of the intermediate frame. We derived Euler-Lagrange equations and showed an efficient numerical scheme that can be implemented on graphics hardware. Finally, a motion compensated frame rate doubling version of our method is implemented. We evaluate the quality of both 90 and 100% of the frames for medical diagnosis domain through objective image quality metrics. Our method improves state-of-the-art result for 90% frames while performing equivalent for the remaining cases with other existing methods. In the last section, we show application of frame interpolation to informative frame segment visualization and to reduce the power consumption.

Efficient Algorithms for Real-Time GPU Volumetric Cloud Rendering with Enhanced Geometry

This paper presents several new techniques for volumetric cloud rendering using efficient algorithms and data structures based on ray-tracing methods for cumulus generation, achieving an optimum balance between realism and performance. These techniques target applications such as flight simulations, computer games, and educational software, even with conventional graphics hardware. The contours of clouds are defined by implicit mathematical expressions or triangulated structures inside which volumetric rendering is performed. Novel techniques are used to reproduce the asymmetrical nature of clouds and the effects of light-scattering, with low computing costs. The work includes a new method to create randomized fractal clouds using a recursive grammar. The graphical results are comparable to those produced by state-of-the-art, hyper-realistic algorithms. These methods provide real-time performance, and are superior to particle-based systems. These outcomes suggest that our methods offer a good balance between realism and performance, and are suitable for use in the standard graphics industry.

Dense tracking, mapping and scene labeling using a depth camera

We present a system for dense tracking, 3D reconstruction, and object detection of desktop-like environments, using a depth camera; the Kinect sensor. The camera is moved by hand meanwhile its pose is estimated, and a dense model, with evolving color information of the scene, is constructed. Alternatively, the user can couple the object detection module (YOLO: you only look once [1]) for detecting and propagating to the model information of categories of objects commonly found over desktops, like monitors, keyboards, books, cups, and laptops, getting a model with color associated to object categories. The camera pose is estimated using a model-to-frame technique with a coarse-to-fine iterative closest point algorithm (ICP), achieving a drift-free trajectory, robustness to fast camera motion and to variable lighting conditions. Simultaneously, the depth maps are fused into the volumetric structure from the estimated camera poses. For visualizing an explicit representation of the scene, the marching cubes algorithm is employed. The tracking, fusion, marching cubes, and object detection processes were implemented using commodity graphics hardware for improving the performance of the system. We achieve outstanding results in camera pose, high quality of the model’s color and geometry, and stability in color from the detection module (robustness to wrong detections) and successful management of multiple instances of the same category.

Interactive rendering of light scattering in dust molecules using particle systems

In this paper introduces a technique for rendering effect of the volumetric lighting in dusty atmosphere using particle systems. Despite numerous techniques has been proposed for rendering these effects but still lack realism in the interactive applications. This technique is based on the sampling planes to compute radiance transport equation and use dynamic model of the dust. The scattering of light is computed by using fragment shaders and 2D texture by making use of the graphics hardware, while using ParticleEngine technique generates the dust. The technique is efficient and accurate to mimic a realistic scenes have effect such as scattering of light in dust molecules. In addition to, volumetric shadows are created resulting of density and size particles within participating media. Therefore, scattering of light is generated in presence dusty media that lead to provide visual clue closer to realistic.

Evaluation of a BVH Construction Accelerator Architecture for High-Quality Visualization

The ever-increasing demands of computer graphics applications have motivated the evolution of computer graphics hardware over the last 20 years. Early commodity graphics hardware was largely based on fixed-function components offering little flexibility. The gradual replacement of fixed-function hardware with more general-purpose instruction processors, has enabled GPUs to deliver visual experiences more tailored to specific applications. This trend has culminated in modern GPUs essentially being programmable stream processors, capable of supporting a wide variety of applications in and outside of computer graphics. However, the growing concern of power efficiency in modern processors, coupled with an increasing demand for supporting next-generation graphics pipelines, has re-invigorated the debate on the use of fixed-function accelerators in these platforms. In this paper, we conduct a study of a heterogeneous, system-on-chip solution for the construction of a highly important data structure for computer graphics: the bounding volume hierarchy. This design incorporates conventional CPU cores alongside a fixed-function accelerator prototyped on a reconfigurable logic fabric. Our study supports earlier, simulation-only studies which argue for the introduction of this class of accelerator in future graphics processors.

An Efficient Acceleration of Solving Heat and Mass Transfer Equations with the Second Kind Boundary Conditions in Capillary Porous Composite Cylinder Using Programmable Graphics Hardware

With the recent developments in computing technology, increased efforts have gone into simulation of various scientific methods and phenomenon in engineering fields. One such case is the simulation of heat and mass transfer in capillary porous media, which is becoming more and more important in analysing various scenarios in engineering applications. Analysing such heat and mass transfer phenomenon in a given environment requires us to simulate it. This entails simulation of coupled heat mass transfer equations. However, this process of numerical solution of heat and mass transfer equations is very much time consuming. Therefore, this paper aims at utilizing one of the acceleration techniques developed in the graphics community that exploits a graphics processing unit (GPU) which is applied to the numerical solutions of heat and mass transfer equations. The nVidia Compute Unified Device Architecture (CUDA) programming model caters a good method of applying parallel computing to program the graphical processing unit. This paper shows a good improvement in the performance while solving the heat and mass transfer equations for capillary porous composite cylinder with the second kind of boundary conditions numerically running on GPU. This heat and mass transfer simulation is implemented using CUDA platform on nVidia Quadro FX 4800 graphics card. Our experimental results depict the drastic performance improvement when GPU is used to perform heat and mass transfer simulation. GPU can significantly accelerate the performance with a maximum observed speedup of more than 7-fold times. Therefore, the GPU is a good approach to accelerate the heat and mass transfer simulation.

Interactive rendering of light scattering in dust molecules using particle systems

In this paper introduces a technique for rendering effect of the volumetric lighting in dusty atmosphere using particle systems. Despite numerous techniques has been proposed for rendering these effects but still lack realism in the interactive applications. This technique is based on the sampling planes to compute radiance transport equation and use dynamic model of the dust. The scattering of light is computed by using fragment shaders and 2D texture by making use of the graphics hardware, while using ParticleEngine technique generates the dust. The technique is efficient and accurate to mimic a realistic scenes have effect such as scattering of light in dust molecules. In addition to, volumetric shadows are created resulting of density and size particles within participating media. Therefore, scattering of light is generated in presence dusty media that lead to provide visual clue closer to realistic.

A new approach to fluid–structure interaction within graphics hardware accelerated smooth particle hydrodynamics considering heterogeneous particle size distribution

A corrective smooth particle method (CSPM) within smooth particle hydrodynamics (SPH) is used to study the deformation of an aircraft structure under high-velocity water-ditching impact load. The CSPM-SPH method features a new approach for the prediction of two-way fluid–structure interaction coupling. Results indicate that the implementation is well suited for modeling the deformation of structures under high-velocity impact into water as evident from the predicted stress and strain localizations in the aircraft structure as well as the integrity of the impacted interfaces, which show no artificial particle penetrations. To reduce the simulation time, a heterogeneous particle size distribution over a complex three-dimensional geometry is used. The variable particle size is achieved from a finite element mesh with variable element size and, as a result, variable nodal (i.e., SPH particle) spacing. To further accelerate the simulations, the SPH code is ported to a graphics processing unit using the OpenACC standard. The implementation and simulation results are described and discussed in this paper.

Accelerated Deconvolution of Radio Interferometric Images using Orthogonal Matching Pursuit and Graphics Hardware

Deconvolution of native radio interferometric images constitutes a major computational component of the imaging process. An efficient and robust deconvolution operation is essential for reconstruction of the true sky signal from measured telescopic data. The techniques of compressed sensing provide a mathematically-rigorous framework within which to implement deconvolution of images formed from a sparse set of nearly-random measurements. We present an accelerated implementation of the orthogonal matching pursuit (OMP) algorithm (a compressed sensing method) that makes use of graphics processing unit (GPU) hardware. We show that OMP correctly identifies more sources than CLEAN, identifying up to 82% of the sources in 100 test images, while CLEAN only identifies up to 61% of the sources. In addition, the residual after source extraction is [Formula: see text] times lower for OMP than for CLEAN. Furthermore, the graphics implementation of OMP performs around 23 times faster than a 4-core CPU.

GPU-accelerated locally injective shape deformation

We present a highly efficient planar meshless shape deformation algorithm. Our method is based on an unconstrained minimization of isometric energies, and is guaranteed to produce C ∞ locally injective maps by operating within a reduced dimensional subspace of harmonic maps. We extend the harmonic subspace of [Chen and Weber 2015] to support multiply-connected domains, and further provide a generalization of the bounded distortion theorem that appeared in that paper. Our harmonic map, as well as the gradient and the Hessian of our isometric energies possess closed-form expressions. A key result is a simple-and-fast analytic modification of the Hessian of the energy such that it is positive definite, which is crucial for the successful operation of a Newton solver. The method is straightforward to implement and is specifically designed to harness the processing power of modern graphics hardware. Our modified Newton iterations are shown to be extremely effective, leading to fast convergence after a handful of iterations, while each iteration is fast due to a combination of a number of factors, such as the smoothness and the low dimensionality of the subspace, the closed-form expressions for the differentials, and the avoidance of expensive strategies to ensure positive definiteness. The entire pipeline is carried out on the GPU, leading to deformations that are significantly faster to compute than the state-of-the-art.

Computing the Distance between Two Finite Element Solutions Defined on Different 3D Meshes on a GPU

This article introduces a new method to efficiently compute the distance (i.e., $L^p$ norm of the difference) between two functions supported by two different meshes of the same 3D domain. The functions that we consider are typically finite element solutions discretized in different function spaces supported by meshes that are potentially completely unrelated. Our method computes an approximation of the distance by resampling both fields over a set of parallel 2D regular grids. By leveraging the parallel horse power of computer graphics hardware (graphics processing unit (GPU)), our method can efficiently compute distances between meshes with multimillion elements in seconds. We demonstrate our method applied to different problems (distance between known functions, Poisson solutions, and linear elasticity solutions) using different function spaces (Lagrange polynomials from order one to seven) and different meshes (tetrahedral and hexahedral, with linear or quadratic geometry).