3D Rasterization: a Bridge Between Rasterization and Ray Casting
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Volume Rendering
Volume Rendering 1.1. Introduction Rapid advances in hardware have been transforming revolutionary approaches in computer graphics into reality. One typical example is the raster graphics that took place in the seventies, when hardware innovations enabled the transition from vector graphics to raster graphics. Another example which has a similar potential is currently shaping up in the field of volume graphics. This trend is rooted in the extensive research and development effort in scientific visualization in general and in volume visualization in particular. Visualization is the usage of computer-supported, interactive, visual representations of data to amplify cognition. Scientific visualization is the visualization of physically based data. Volume visualization is a method of extracting meaningful information from volumetric datasets through the use of interactive graphics and imaging, and is concerned with the representation, manipulation, and rendering of volumetric datasets. Its objective is to provide mechanisms for peering inside volumetric datasets and to enhance the visual understanding. Traditional 3D graphics is based on surface representation. Most common form is polygon-based surfaces for which affordable special-purpose rendering hardware have been developed in the recent years. Volume graphics has the potential to greatly advance the field of 3D graphics by offering a comprehensive alternative to conventional surface representation methods. The object of this thesis is to examine the existing methods for volume visualization and to find a way of efficiently rendering scientific data with commercially available hardware, like PC’s, without requiring dedicated systems. 1.2. Volume Rendering Our display screens are composed of a two-dimensional array of pixels each representing a unit area. -
Graphics Pipeline and Rasterization
Graphics Pipeline & Rasterization Image removed due to copyright restrictions. MIT EECS 6.837 – Matusik 1 How Do We Render Interactively? • Use graphics hardware, via OpenGL or DirectX – OpenGL is multi-platform, DirectX is MS only OpenGL rendering Our ray tracer © Khronos Group. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. 2 How Do We Render Interactively? • Use graphics hardware, via OpenGL or DirectX – OpenGL is multi-platform, DirectX is MS only OpenGL rendering Our ray tracer © Khronos Group. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. • Most global effects available in ray tracing will be sacrificed for speed, but some can be approximated 3 Ray Casting vs. GPUs for Triangles Ray Casting For each pixel (ray) For each triangle Does ray hit triangle? Keep closest hit Scene primitives Pixel raster 4 Ray Casting vs. GPUs for Triangles Ray Casting GPU For each pixel (ray) For each triangle For each triangle For each pixel Does ray hit triangle? Does triangle cover pixel? Keep closest hit Keep closest hit Scene primitives Pixel raster Scene primitives Pixel raster 5 Ray Casting vs. GPUs for Triangles Ray Casting GPU For each pixel (ray) For each triangle For each triangle For each pixel Does ray hit triangle? Does triangle cover pixel? Keep closest hit Keep closest hit Scene primitives It’s just a different orderPixel raster of the loops! -
Rendering of Feature-Rich Dynamically Changing Volumetric Datasets on GPU
Procedia Computer Science Volume 29, 2014, Pages 648–658 ICCS 2014. 14th International Conference on Computational Science Rendering of Feature-Rich Dynamically Changing Volumetric Datasets on GPU Martin Schreiber, Atanas Atanasov, Philipp Neumann, and Hans-Joachim Bungartz Technische Universit¨at M¨unchen, Munich, Germany [email protected],[email protected],[email protected],[email protected] Abstract Interactive photo-realistic representation of dynamic liquid volumes is a challenging task for today’s GPUs and state-of-the-art visualization algorithms. Methods of the last two decades consider either static volumetric datasets applying several optimizations for volume casting, or dynamic volumetric datasets with rough approximations to realistic rendering. Nevertheless, accurate real-time visualization of dynamic datasets is crucial in areas of scientific visualization as well as areas demanding for accurate rendering of feature-rich datasets. An accurate and thus realistic visualization of such datasets leads to new challenges: due to restrictions given by computational performance, the datasets may be relatively small compared to the screen resolution, and thus each voxel has to be rendered highly oversampled. With our volumetric datasets based on a real-time lattice Boltzmann fluid simulation creating dynamic cavities and small droplets, existing real-time implementations are not applicable for a realistic surface extraction. This work presents a volume tracing algorithm capable of producing multiple refractions which is also robust to small droplets and cavities. Furthermore we show advantages of our volume tracing algorithm compared to other implementations. Keywords: 1 Introduction The photo-realistic real-time rendering of dynamic liquids, represented by free surface flows and volumetric datasets, has been studied in numerous works [13, 9, 10, 14, 18]. -
Ray Casting Architectures for Volume Visualization
Ray Casting Architectures for Volume Visualization The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Ray, Harvey, Hanspeter Pfister, Deborah Silver, and Todd A. Cook. 1999. Ray casting architectures for volume visualization. IEEE Transactions on Visualization and Computer Graphics 5(3): 210-223. Published Version doi:10.1109/2945.795213 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:4138553 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Ray Casting Architectures for Volume Visualization Harvey Ray, Hansp eter P ster , Deb orah Silver , Todd A. Co ok Abstract | Real-time visualization of large volume datasets demands high p erformance computation, pushing the stor- age, pro cessing, and data communication requirements to the limits of current technology. General purp ose paral- lel pro cessors have b een used to visualize mo derate size datasets at interactive frame rates; however, the cost and size of these sup ercomputers inhibits the widespread use for real-time visualization. This pap er surveys several sp e- cial purp ose architectures that seek to render volumes at interactive rates. These sp ecialized visualization accelera- tors have cost, p erformance, and size advantages over par- allel pro cessors. All architectures implement ray casting using parallel and pip elined hardware. Weintro duce a new metric that normalizes p erformance to compare these ar- Fig. -
Ray Tracing Height Fields
Ray Tracing Height Fields £ £ £ Huamin Qu£ Feng Qiu Nan Zhang Arie Kaufman Ming Wan † £ Center for Visual Computing (CVC) and Department of Computer Science State University of New York at Stony Brook, Stony Brook, NY 11794-4400 †The Boeing Company, P.O. Box 3707, M/C 7L-40, Seattle, WA 98124-2207 Abstract bility, make the ray tracing approach a promising alterna- tive for rasterization approach when the size of the terrain We present a novel surface reconstruction algorithm is very large [13]. More importantly, ray tracing provides which can directly reconstruct surfaces with different levels more flexibility than hardware rendering. For example, ray of smoothness in one framework from height fields using 3D tracing allows us to operate directly on the image/Z-buffer discrete grid ray tracing. Our algorithm exploits the 2.5D to render special effects such as terrain with underground nature of the elevation data and the regularity of the rect- bunkers, terrain with shadows, and flythrough with a fish- angular grid from which the height field surface is sampled. eye view. In addition, it is easy to incorporate clouds, haze, Based on this reconstruction method, we also develop a hy- flames, and other amorphous phenomena into the scene by brid rendering method which has the features of both ras- ray tracing. Ray tracing can also be used to fill in holes in terization and ray tracing. This hybrid method is designed image-based rendering. to take advantage of GPUs newly available flexibility and processing power. Most ray tracing height field papers [2, 4, 8, 10] focused on fast ray traversal algorithms and antialiasing methods. -
A Survey of Volumetric Visualization Techniques for Medical Images
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Volume 2, Issue 4, April 2015, PP 34-39 ISSN 2349-4840 (Print) & ISSN 2349-4859 (Online) www.arcjournals.org A Survey of Volumetric Visualization Techniques for Medical Images S. Jagadesh Babu Vidya Vikas Institute of Technology, Chevella, Hyderabad, India Abstract: Medical Image Visualization provides a better visualization for doctors in clinical diagnosis, surgery operation, leading treatment and so on. It aims at a visual representation of the full dataset, of all images at the same time. The main issue is to select the most appropriate image rendering method, based on the acquired data and the medical relevance. The paper presents a review of some significant work in the area of volumetric visualization. An overview of various algorithms and analysis are provided with their assumptions, advantages and limitations, so that the user can choose the better technique to detect particular defects in any small region of the body parts which helps the doctors for more accurate and proper diagnosis of different medical ailments. Keywords: Medical Imaging, Volume Visualization, Isosurface, Surface Extraction, Direct Volume Rendering. 1. INTRODUCTION Visualization in medicine or medical visualization [1] is a special area of scientific visualization that established itself as a research area in the late 1980s. Medical visualization [1,9] is based on computer graphics, which provide representations to store 3D geometry and efficient algorithms to render such representations. Additional influence comes from image processing, which basically defined the field of medical image analysis (MIA). MIA, however, is originally the processing of 2D images, while its 3D extension was traditionally credited to medical visualization. -
Ray Casting and Rendering
MIT EECS 6.837 Computer Graphics Part 2 – Rendering Today: Intro to Rendering, Ray Casting © NVIDIA Inc. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. NVIDIA MIT EECS 6.837 – Matusik 1 Cool Artifacts from Assignment 1 © source unknown. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. 2 Cool Artifacts from Assignment 1 © source unknown. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. 3 The Story So Far • Modeling – splines, hierarchies, transformations, meshes, etc. • Animation – skinning, ODEs, masses and springs • Now we’ll to see how to generate an image given a scene description! 4 The Remainder of the Term • Ray Casting and Ray Tracing • Intro to Global Illumination – Monte Carlo techniques, photon mapping, etc. • Shading, texture mapping – What makes materials look like they do? • Image-based Rendering • Sampling and antialiasing • Rasterization, z-buffering • Shadow techniques • Graphics Hardware © ACM. All rights reserved. This content is excluded from our Creative Commons [Lehtinen et al. 2008] license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. 5 Today • What does rendering mean? • Basics of ray casting 6 © source unknown. All rights reserved. This content is excluded from our Creative Commons license. For more information, see http://ocw.mit.edu/help/faq-fair-use/. © Oscar Meruvia-Pastor, Daniel Rypl. All rights reserved. -
A Survey on Bounding Volume Hierarchies for Ray Tracing
DOI: 10.1111/cgf.142662 EUROGRAPHICS 2021 Volume 40 (2021), Number 2 H. Rushmeier and K. Bühler STAR – State of The Art Report (Guest Editors) A Survey on Bounding Volume Hierarchies for Ray Tracing yDaniel Meister1z yShinji Ogaki2 Carsten Benthin3 Michael J. Doyle3 Michael Guthe4 Jiríˇ Bittner5 1The University of Tokyo 2ZOZO Research 3Intel Corporation 4University of Bayreuth 5Czech Technical University in Prague Figure 1: Bounding volume hierarchies (BVHs) are the ray tracing acceleration data structure of choice in many state of the art rendering applications. The figure shows a ray-traced scene, with a visualization of the otherwise hidden structure of the BVH (left), and a visualization of the success of the BVH in reducing ray intersection operations (right). Abstract Ray tracing is an inherent part of photorealistic image synthesis algorithms. The problem of ray tracing is to find the nearest intersection with a given ray and scene. Although this geometric operation is relatively simple, in practice, we have to evaluate billions of such operations as the scene consists of millions of primitives, and the image synthesis algorithms require a high number of samples to provide a plausible result. Thus, scene primitives are commonly arranged in spatial data structures to accelerate the search. In the last two decades, the bounding volume hierarchy (BVH) has become the de facto standard acceleration data structure for ray tracing-based rendering algorithms in offline and recently also in real-time applications. In this report, we review the basic principles of bounding volume hierarchies as well as advanced state of the art methods with a focus on the construction and traversal. -
Computer Graphics (CS 543) Lecture 12: Part 2 Ray Tracing (Part 1) Prof
Computer Graphics (CS 543) Lecture 12: Part 2 Ray Tracing (Part 1) Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) Raytracing Global illumination‐based rendering method Simulates rays of light, natural lighting effects Because light path is traced, handles effects tough for openGL: Shadows Multiple inter‐reflections Transparency Refraction Texture mapping Newer variations… e.g. photon mapping (caustics, participating media, smoke) Note: raytracing can be semester graduate course Today: start with high‐level description Raytracing Uses Entertainment (movies, commercials) Games (pre‐production) Simulation (e.g. military) Image: Internet Ray Tracing Contest Winner (April 2003) How Raytracing Works OpenGL is object space rendering start from world objects, rasterize them Ray tracing is image space method Start from pixel, what do you see through this pixel? Looks through each pixel (e.g. 640 x 480) Determines what eye sees through pixel Basic idea: Trace light rays: eye ‐> pixel (image plane) ‐> scene If a ray intersect any scene object in this direction Yes? render pixel using object color No? it uses the background color Automatically solves hidden surface removal problem Case A: Ray misses all objects Case B: Ray hits an object Case B: Ray hits an object . Ray hits object: Check if hit point is in shadow, build secondary ray (shadow ray) towards light sources. Case B: Ray hits an object .If shadow ray hits another object before light source: first intersection point is in shadow of the second object. Otherwise, collect light contributions Case B: Ray hits an object .First Intersection point in the shadow of the second object is the shadow area. -
Ray Casting Architectures for Volume Visualization
MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Ray Casting Architectures for Volume Visualization Harvey Ray, Hanspeter Pfister, Deborah Silver, Todd A. Cook TR99-17 April 1999 Abstract Real-time visualization of large volume datasets demands high performance computation, push- ing the storage, processing, and data communication requirements to the limits of current tech- nology. General purpose parallel processors have been used to visualize moderate size datasets at interactive frame rates; however, the cost and size of these supercomputers inhibits the widespread use for real-time visualization. This paper surveys several special purpose architectures that seek to render volumes at interactive rates. These specialized visualization accelerators have cost, per- formance, and size advantages over parallel processors. All architectures implement ray casting using parallel and pipelined hardware. We introduce a new metric that normalizes performance to compare these architectures. The architectures included in this survey are VOGUE, VIRIM, Array Based Ray Casting, EM-Cube, and VIZARD II. We also discuss future applications of special purpose accelerators. IEEE Transactions on Visualization and Computer Graphics This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. -
Ray Casting Architectures for Volume Visualization
Ray Casting Architectures for Volume Visualization Harvey Ray, Hansp eter P ster , Deb orah Silver , Todd A. Co ok Abstract | Real-time visualization of large volume datasets demands high p erformance computation, pushing the stor- age, pro cessing, and data communication requirements to the limits of current technology. General purp ose paral- lel pro cessors have b een used to visualize mo derate size datasets at interactive frame rates; however, the cost and size of these sup ercomputers inhibits the widespread use for real-time visualization. This pap er surveys several sp e- cial purp ose architectures that seek to render volumes at interactive rates. These sp ecialized visualization accelera- tors have cost, p erformance, and size advantages over par- allel pro cessors. All architectures implement ray casting using parallel and pip elined hardware. Weintro duce a new metric that normalizes p erformance to compare these ar- Fig. 1. Volume dataset. chitectures. The architectures included in this survey are VOGUE, VIRIM, Array Based Ray Casting, EM-Cub e, and VIZARD II. We also discuss future applications of sp ecial ume rendering architectures that seek to achieveinteractive purp ose accelerators. volume rendering for rectilinear datasets. A survey of other metho ds used to achieve real time volume rendering is pre- I. Introduction sented in [47]. The motivation for custom volume renderers OLUME visualization is an imp ortant to ol to view is discussed in the next section. Several other custom ar- and analyze large amounts of data from various sci- V chitectures exist [1], [8], [10], [16], [17], [19], [36], [38] but enti c disciplines. -
Proposed Mobile System for Bone Visualization Using Gpu Raycasting
12 International Journal "Information Technologies & Knowledge" Volume 10, Number 1, © 2016 PROPOSED MOBILE SYSTEM FOR BONE VISUALIZATION USING GPU RAYCASTING VOLUME RENDERING TECHNIQUE Yassmin Abdallah, Abdel-Badeeh M.Salem Abstract: Despite the rapid development of mobile phones, the existence of medical visualization applications on stores is rare. This paper represents iOS mobile application that helps medical students and doctors to show bones processed over in an orthopedic surgery. The mobile application implements GPU ray casting algorithm. Experimental results obtained visually by comparing the result to the result obtained from ImageVis3D which use slice based volume rendering technique. ImageVis3D's development was initiated in 2007 by the NIH/NCRR Center for Integrative Biomedical Computing and additionally supported by the DOE Visualization and Analytics Center for Enabling Technologies at the SCI Institute. The result shows that proposed application based on GPU ray- casting technique present better visualized result than ImageVis3D. The dataset used in the experiment is CT images obtained from Osirix datasets for surgical repair of facial deformity. Keywords: mHealth, volume visualization, mobile-based biomedical computing , CT images , GPU ray casting ACM Classification Keywords: D.2: SOFTWARE ENGINEERING , I.3: COMPUTER GRAPHICS , J.3: LIFE AND MEDICAL SCIENCES Introduction During common orthopedic surgery training, students must learn how to perform numerous surgical procedures like fixing fractures which requires training on artificial bones with the usage of surgical tools and implants. These artificial bones have a high cost that depends on the bone's type and quality. Thus the idea of using a computer based simulators for orthopedic surgery training appeared. Simulators will decrease the cost and help students to practice various procedures on a large number of available simulated surgeries in a safe and controlled environment.