Ricardo Marroquim

Flow-Based Local Optimization for Image-to-Geometry Projection

The projection of a photographic data set on a 3D model is a robust and widely applicable way to acquire appearance information of an object. The first step of this procedure is the alignment of the images on the 3D model. While any reconstruction pipeline aims at avoiding misregistration by improving camera calibrations and geometry, in practice a perfect alignment cannot always be reached. Depending on the way multiple camera images are fused on the object surface, remaining misregistrations show up either as ghosting or as discontinuities at transitions from one camera view to another. In this paper we propose a method, based on the computation of Optical Flow between overlapping images, to correct the local misalignment by determining the necessary displacement. The goal is to correct the symptoms of misregistration, instead of searching for a globally consistent mapping, which might not exist. The method scales up well with the size of the data set (both photographic and geometric) and is quite independent of the characteristics of the 3D model (topology cleanliness, parametrization, density). The method is robust and can handle real world cases that have different characteristics: low level geometric details and images that lack enough features for global optimization or manual methods. It can be applied to different mapping strategies, such as texture or per-vertex attribute encoding.

Introduction to GPU Programming with GLSL

One of the challenging advents in Computer Science in recent years was the fast evolution of parallel processors, specially the GPU – graphics processing unit. GPUs today play a major role in many computational environments, most notably those regarding real-time graphics applications, such as games. The digital game industry is one of the main driving forces behind GPUs, it persistently elevates the state-of-art in Computer Graphics, pushing outstanding realistic scenes to interactive levels. The evolution of photo realistic scenes consequently demands better graphics cards from the hardware industry. Over the last decade, the hardware has not only become a hundred times more powerful, but has also become increasingly customizable allowing programmers to alter some of previously fixed functionalities. This tutorial is an introduction to GPU programming using the OpenGL Shading Language – GLSL. It comprises an overview of graphics concepts and a walk-through the graphics card rendering pipeline. A thorough understanding of the graphics pipeline is extremely important when designing a program in GPU, known as a shader. Throughout this tutorial, the exposition of the GLSL language and GPU programming details are followed closely by examples ranging from very simple to more practical applications. It is aimed at an audience with no or little knowledge on the subject.

Hardware-assisted projected tetrahedra

We present a flexible and highly efficient hardware‐assisted volume renderer grounded on the original Projected Tetrahedra (PT) algorithm. Unlike recent similar approaches, our method is exclusively based on the rasterization of simple geometric primitives and takes full advantage of graphics hardware. Both vertex and geometry shaders are used to compute the tetrahedral projection, while the volume ray integral is evaluated in a fragment shader; hence, volume rendering is performed entirely on the GPU within a single pass through the pipeline. We apply a CUDA‐based visibility ordering achieving rendering and sorting performance of over 6 M Tet/s for unstructured datasets. Furthermore, as each tetrahedron is processed independently, we employ a data‐parallel solution which is neither bound by GPU memory size nor does it rely on auxiliary volume information. In addition, iso‐surfaces can be readily extracted during the rendering process, and time‐varying data are handled without extra burden.

Efficient Point-Based Rendering Using Image Reconstruction

Image-space reconstruction of continuous surfaces from scattered one-pixel projections of points is known to potentially offer an advantageous time complexity compared to surface splatting techniques. We propose a new algorithm for hardware-accelerated image-space reconstruction using pull-push interpolation and present an efficient GPU implementation. Compared to published image-space reconstruction approaches employing the pull-push interpolation, our method offers a significantly improved image quality because of the integration of elliptic boxfilters and support for deferred Phong shading. For large point-based models, our GPU implementation is capable of rendering more than 50M points per second—including image-space reconstruction and deferred shading.

Volume and Isosurface Rendering with GPU-Accelerated Cell Projection*

We present an efficient Graphics Processing Unit GPU‐based implementation of the Projected Tetrahedra (PT) algorithm. By reducing most of the CPU–GPU data transfer, the algorithm achieves interactive frame rates (up to 2.0 M Tets/s) on current graphics hardware. Since no topology information is stored, it requires substantially less memory than recent interactive ray casting approaches. The method uses a two‐pass GPU approach with two fragment shaders. This work includes extended volume inspection capabilities by supporting interactive transfer function editing and isosurface highlighting using a Phong illumination model.

GPU-Based Cell Projection for Interactive Volume Rendering

We present a practical approach for implementing the projected tetrahedra (PT) algorithm for interactive volume rendering of unstructured data using programmable graphics cards. Unlike similar works reported earlier, our method employs two fragment shaders, one for computing the tetrahedra projections and another for rendering the elements. We achieve interactive rates by storing the model in texture memory and avoiding redundant projections of implementations using vertex shaders. Our algorithm is capable of rendering over 2.0 M Tet/s on current graphics hardware, making it competitive with recent ray-casting approaches, while occupying a substantially smaller memory footprint

Parallel Image Segmentation Using Reduction-Sweeps on Multicore Processors and GPUs

In this paper we introduce the Reduction Sweep algorithm, a novel graph-based image segmentation algorithm that is designed for easy parallelization. It is based on a clustering approach focusing on local image characteristics. Each pixel is compared with its neighbors in an implicitly independent manner, and those deemed sufficiently similar according to a color criterion are joined. We achieve fast execution times while still maintaining the visual quality of the results. The algorithm is presented in four different implementations: sequential CPU, parallel CPU, GPU, and hybrid CPU-GPU. We compare the execution times of the four versions with each other and with other closely related image segmentation algorithms.

Special Section: Point-Based Graphics: Efficient image reconstruction for point-based and line-based rendering

We address the problem of an efficient image-space reconstruction of adaptively sampled scenes in the context of point-based and line-based graphics. The image-space reconstruction offers an advantageous time complexity compared to surface splatting techniques and, in fact, our improved GPU implementation performs significantly better than splatting implementations for large point-based models. We discuss the integration of elliptical Gaussian weights for enhanced image quality and generalize the image-space reconstruction to line segments. Furthermore, we present solutions for the efficient combination of points, lines, and polygons in a single image.

Interactive cutaways of oil reservoirs

Abstract In the Oil and Gas industry, processing and visualizing 3D models is of paramount importance for making exploratory and production decisions. Hydrocarbons reservoirs are entities buried deep in the earth’s crust, and a simplified 3D geological model that mimics this environment is generated to run simulations and help understand geological and physical concepts. For the task of visually inspecting these models, we advocate the use of Cutaways: an illustrative technique to emphasize important structures or parts of the model by selectively discarding occluding parts, while keeping the contextual information. However, the complexity of reservoir models imposes severe restrictions and limitations when using generic illustrative techniques previously proposed by the computer graphics community. To overcome this challenge, we propose an interactive Cutaway method, strongly relying on screen-space GPU techniques, specially designed for inspecting 3D reservoir models represented as corner-point grids, the industry’s standard.

Multi-resolution triangulations with adaptation to the domain based on physical compression

This paper presents a method for generating multi-resolution triangulations of non-manifold objects composed of several regions with arbitrary geometry. The process of adapting the triangulation to the boundary of the object is based on physical compression, more specifically, a mass-spring system. The final triangulation usually has no degenerated triangles and provides an approximation of the boundary based on a chosen resolution.