Light (Technical)
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Path Tracing
Path Tracing Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017 Irradiance Circumference of a Circle • The circumference of a circle of radius r is 2πr • In fact, a radian is defined as the angle you get on an arc of length r • We can represent the circumference of a circle as an integral 2휋 푐푖푟푐 = 푟푑휑 0 • This is essentially computing the length of the circumference as an infinite sum of infinitesimal segments of length 푟푑휑, over the range from 휑=0 to 2π Area of a Hemisphere • We can compute the area of a hemisphere by integrating ‘rings’ ranging over a second angle 휃, which ranges from 0 (at the north pole) to π/2 (at the equator) • The area of a ring is the circumference of the ring times the width 푟푑휃 • The circumference is going to be scaled by sin휃 as the rings are smaller towards the top of the hemisphere 휋 2 2휋 2 2 푎푟푒푎 = sin 휃 푟 푑휑 푑휃 = 2휋푟 0 0 Hemisphere Integral 휋 2 2휋 2 푎푟푒푎 = sin 휃 푟 푑휑 푑휃 0 0 • We are effectively computing an infinite summation of tiny rectangular area elements over a two dimensional domain. Each element has dimensions: sin 휃 푟푑휑 × 푟푑휃 Irradiance • Now, let’s assume that we are interested in computing the total amount of light arriving at some point on a surface • We are essentially integrating over all possible directions in the hemisphere above the surface (assuming it’s opaque and we’re not receiving translucent light from below the surface) • We are integrating the light intensity (or radiance) coming in from every direction • The total incoming radiance over all directions in the hemisphere -
Surface Recovery: Fusion of Image and Point Cloud
Surface Recovery: Fusion of Image and Point Cloud Siavash Hosseinyalamdary Alper Yilmaz The Ohio State University 2070 Neil avenue, Columbus, Ohio, USA 43210 pcvlab.engineering.osu.edu Abstract construct surfaces. Implicit (or volumetric) representation of a surface divides the three dimensional Euclidean space The point cloud of the laser scanner is a rich source of to voxels and the value of each voxel is defined based on an information for high level tasks in computer vision such as indicator function which describes the distance of the voxel traffic understanding. However, cost-effective laser scan- to the surface. The value of every voxel inside the surface ners provide noisy and low resolution point cloud and they has negative sign, the value of the voxels outside the surface are prone to systematic errors. In this paper, we propose is positive and the surface is represented as zero crossing two surface recovery approaches based on geometry and values of the indicator function. Unfortunately, this repre- brightness of the surface. The proposed approaches are sentation is not applicable to open surfaces and some mod- tested in realistic outdoor scenarios and the results show ifications should be applied to reconstruct open surfaces. that both approaches have superior performance over the- The least squares and partial differential equations (PDE) state-of-art methods. based approaches have also been developed to implicitly re- construct surfaces. The moving least squares(MLS) [22, 1] and Poisson surface reconstruction [16], has been used in 1. Introduction this paper for comparison, are particularly popular. Lim and Haron review different surface reconstruction techniques in Point cloud is a valuable source of information for scene more details [20]. -
Experimental Validation of Autodesk 3Ds Max Design 2009 and Daysim
Experimental Validation of Autodesk® 3ds Max® Design 2009 and Daysim 3.0 NRC Project # B3241 Submitted to: Autodesk Canada Co. Media & Entertainment Submitted by: Christoph Reinhart1,2 1) National Research Council Canada - Institute for Research in Construction (NRC-IRC) Ottawa, ON K1A 0R6, Canada (2001-2008) 2) Harvard University, Graduate School of Design Cambridge, MA 02138, USA (2008 - ) February 12, 2009 B3241.1 Page 1 Table of Contents Abstract ....................................................................................................................................... 3 1 Introduction .......................................................................................................................... 3 2 Methodology ......................................................................................................................... 5 2.1 Daylighting Test Cases .................................................................................................... 5 2.2 Daysim Simulations ....................................................................................................... 12 2.3 Autodesk 3ds Max Design Simulations ........................................................................... 13 3 Results ................................................................................................................................ 14 3.1 Façade Illuminances ...................................................................................................... 14 3.2 Base Case (TC1) and Lightshelf (TC2) -
Adjoints and Importance in Rendering: an Overview
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 9, NO. 3, JULY-SEPTEMBER 2003 1 Adjoints and Importance in Rendering: An Overview Per H. Christensen Abstract—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. Index Terms—Rendering, adjoints, importance, light, ray tracing, global illumination, participating media, literature survey. æ 1INTRODUCTION HE use of importance functions started in neutron importance since it indicates how much the different parts Ttransport simulations soon after World War II. Im- of the domain contribute to the solution at the most portance was used (in different disguises) from 1983 to important part. Importance is also known as visual accelerate ray tracing [2], [16], [27], [78], [79]. Smits et al. [67] importance, view importance, potential, visual potential, value, formally introduced the use of importance for global -
Open Source Software for Daylighting Analysis of Architectural 3D Models
19th International Congress on Modelling and Simulation, Perth, Australia, 12–16 December 2011 http://mssanz.org.au/modsim2011 Open Source Software for Daylighting Analysis of Architectural 3D Models Terrance Mc Minn a a Curtin University of Technology School of Built Environment, Perth, Australia Email: [email protected] Abstract:This paper examines the viability of using open source software for the architectural analysis of solar access and over shading of building projects. For this paper open source software also includes freely available closed source software. The Computer Aided Design software – Google SketchUp (Free) while not open source, is included as it is freely available, though with restricted import and export abilities. A range of software tools are used to provide an effective procedure to aid the Architect in understanding the scope of sun penetration and overshadowing on a site and within a project. The technique can be also used lighting analysis of both external (to the building) as well as for internal spaces. An architectural model built in SketchUp (free) CAD software is exported in two different forms for the Radiance Lighting Simulation Suite to provide the lighting analysis. The different exports formats allow the 3D CAD model to be accessed directly via Radiance for full lighting analysis or via the Blender Animation program for a graphical user interface limited option analysis. The Blender Modelling Environment for Architecture (BlendME) add-on exports the model and runs Radiance in the background. Keywords:Lighting Simulation, Open Source Software 3226 McMinn, T., Open Source Software for Daylighting Analysis of Architectural 3D Models INTRODUCTION The use of daylight in buildings has the potential for reduction in the energy demands and increasing thermal comfort and well being of the buildings occupants (Cutler, Sheng, Martin, Glaser, et al., 2008), (Webb, 2006), (Mc Minn & Karol, 2010), (Yancey, n.d.) and others. -
An Advanced Path Tracing Architecture for Movie Rendering
RenderMan: An Advanced Path Tracing Architecture for Movie Rendering PER CHRISTENSEN, JULIAN FONG, JONATHAN SHADE, WAYNE WOOTEN, BRENDEN SCHUBERT, ANDREW KENSLER, STEPHEN FRIEDMAN, CHARLIE KILPATRICK, CLIFF RAMSHAW, MARC BAN- NISTER, BRENTON RAYNER, JONATHAN BROUILLAT, and MAX LIANI, Pixar Animation Studios Fig. 1. Path-traced images rendered with RenderMan: Dory and Hank from Finding Dory (© 2016 Disney•Pixar). McQueen’s crash in Cars 3 (© 2017 Disney•Pixar). Shere Khan from Disney’s The Jungle Book (© 2016 Disney). A destroyer and the Death Star from Lucasfilm’s Rogue One: A Star Wars Story (© & ™ 2016 Lucasfilm Ltd. All rights reserved. Used under authorization.) Pixar’s RenderMan renderer is used to render all of Pixar’s films, and by many 1 INTRODUCTION film studios to render visual effects for live-action movies. RenderMan started Pixar’s movies and short films are all rendered with RenderMan. as a scanline renderer based on the Reyes algorithm, and was extended over The first computer-generated (CG) animated feature film, Toy Story, the years with ray tracing and several global illumination algorithms. was rendered with an early version of RenderMan in 1995. The most This paper describes the modern version of RenderMan, a new architec- ture for an extensible and programmable path tracer with many features recent Pixar movies – Finding Dory, Cars 3, and Coco – were rendered that are essential to handle the fiercely complex scenes in movie production. using RenderMan’s modern path tracing architecture. The two left Users can write their own materials using a bxdf interface, and their own images in Figure 1 show high-quality rendering of two challenging light transport algorithms using an integrator interface – or they can use the CG movie scenes with many bounces of specular reflections and materials and light transport algorithms provided with RenderMan. -
Getting Started (Pdf)
GETTING STARTED PHOTO REALISTIC RENDERS OF YOUR 3D MODELS Available for Ver. 1.01 © Kerkythea 2008 Echo Date: April 24th, 2008 GETTING STARTED Page 1 of 41 Written by: The KT Team GETTING STARTED Preface: Kerkythea is a standalone render engine, using physically accurate materials and lights, aiming for the best quality rendering in the most efficient timeframe. The target of Kerkythea is to simplify the task of quality rendering by providing the necessary tools to automate scene setup, such as staging using the GL real-time viewer, material editor, general/render settings, editors, etc., under a common interface. Reaching now the 4th year of development and gaining popularity, I want to believe that KT can now be considered among the top freeware/open source render engines and can be used for both academic and commercial purposes. In the beginning of 2008, we have a strong and rapidly growing community and a website that is more "alive" than ever! KT2008 Echo is very powerful release with a lot of improvements. Kerkythea has grown constantly over the last year, growing into a standard rendering application among architectural studios and extensively used within educational institutes. Of course there are a lot of things that can be added and improved. But we are really proud of reaching a high quality and stable application that is more than usable for commercial purposes with an amazing zero cost! Ioannis Pantazopoulos January 2008 Like the heading is saying, this is a Getting Started “step-by-step guide” and it’s designed to get you started using Kerkythea 2008 Echo. -
Sony Pictures Imageworks Arnold
Sony Pictures Imageworks Arnold CHRISTOPHER KULLA, Sony Pictures Imageworks ALEJANDRO CONTY, Sony Pictures Imageworks CLIFFORD STEIN, Sony Pictures Imageworks LARRY GRITZ, Sony Pictures Imageworks Fig. 1. Sony Imageworks has been using path tracing in production for over a decade: (a) Monster House (©2006 Columbia Pictures Industries, Inc. All rights reserved); (b) Men in Black III (©2012 Columbia Pictures Industries, Inc. All Rights Reserved.) (c) Smurfs: The Lost Village (©2017 Columbia Pictures Industries, Inc. and Sony Pictures Animation Inc. All rights reserved.) Sony Imageworks’ implementation of the Arnold renderer is a fork of the and robustness of path tracing indicated to the studio there was commercial product of the same name, which has evolved independently potential to revisit the basic architecture of a production renderer since around 2009. This paper focuses on the design choices that are unique which had not evolved much since the seminal Reyes paper [Cook to this version and have tailored the renderer to the specic requirements of et al. 1987]. lm rendering at our studio. We detail our approach to subdivision surface After an initial period of co-development with Solid Angle, we tessellation, hair rendering, sampling and variance reduction techniques, decided to pursue the evolution of the Arnold renderer indepen- as well as a description of our open source texturing and shading language components. We also discuss some ideas we once implemented but have dently from the commercially available product. This motivation since discarded to highlight the evolution of the software over the years. is twofold. The rst is simply pragmatic: software development in service of lm production must be responsive to tight deadlines CCS Concepts: • Computing methodologies → Ray tracing; (less the lm release date than internal deadlines determined by General Terms: Graphics, Systems, Rendering the production schedule). -
Semantic Segmentation of Surface from Lidar Point Cloud 3
Noname manuscript No. (will be inserted by the editor) Semantic Segmentation of Surface from Lidar Point Cloud Aritra Mukherjee1 · Sourya Dipta Das2 · Jasorsi Ghosh2 · Ananda S. Chowdhury2 · Sanjoy Kumar Saha1 Received: date / Accepted: date Abstract In the field of SLAM (Simultaneous Localization And Mapping) for robot navigation, mapping the environment is an important task. In this regard the Lidar sensor can produce near accurate 3D map of the environment in the format of point cloud, in real time. Though the data is adequate for extracting information related to SLAM, processing millions of points in the point cloud is computationally quite expensive. The methodology presented proposes a fast al- gorithm that can be used to extract semantically labelled surface segments from the cloud, in real time, for direct navigational use or higher level contextual scene reconstruction. First, a single scan from a spinning Lidar is used to generate a mesh of subsampled cloud points online. The generated mesh is further used for surface normal computation of those points on the basis of which surface segments are estimated. A novel descriptor to represent the surface segments is proposed and utilized to determine the surface class of the segments (semantic label) with the help of classifier. These semantic surface segments can be further utilized for geometric reconstruction of objects in the scene, or can be used for optimized tra- jectory planning by a robot. The proposed methodology is compared with number of point cloud segmentation methods and state of the art semantic segmentation methods to emphasize its efficacy in terms of speed and accuracy. -
LIGHT TRANSPORT SIMULATION in REFLECTIVE DISPLAYS By
LIGHT TRANSPORT SIMULATION IN REFLECTIVE DISPLAYS by Zhanpeng Feng, B.S.E.E., M.S.E.E. A Dissertation In ELECTRICAL ENGINEERING DOCTOR OF PHILOSOPHY Dr. Brian Nutter Chair of the Committee Dr. Sunanda Mitra Dr. Tanja Karp Dr. Richard Gale Dr. Peter Westfall Peggy Gordon Miller Dean of the Graduate School May, 2012 Copyright 2012, Zhanpeng Feng Texas Tech University, Zhanpeng Feng, May 2012 ACKNOWLEDGEMENTS The pursuit of my Ph.D. has been a rather long journey. The journey started when I came to Texas Tech ten years ago, then took a change in direction when I went to California to work for Qualcomm in 2006. Over the course, I am privileged to have met the most amazing professionals in Texas Tech and Qualcomm. Without them I would have never been able to finish this dissertation. I begin by thanking my advisor, Dr. Brian Nutter, for introducing me to the brilliant world of research, and teaching me hands on skills to actually get something done. Dr. Nutter sets an example of excellence that inspired me to work as an engineer and researcher for my career. I would also extend my thanks to Dr. Mitra for her breadth and depth of knowledge; to Dr. Karp for her scientific rigor; to Dr. Gale for his expertise in color science and sense of humor; and to Dr. Westfall, for his great mind in statistics. They have provided me invaluable advice throughout the research. My colleagues and supervisors in Qualcomm also gave tremendous support and guidance along the path. Tom Fiske helped me establish my knowledge in optics from ground up and taught me how to use all the tools for optical measurements. -
2014 3-4 Acta Graphica.Indd
Vidmar et al.: Performance Assessment of Three Rendering..., acta graphica 25(2014)3–4, 101–114 author viewpoint acta graphica 234 Performance Assessment of Three Rendering Engines in 3D Computer Graphics Software Authors Žan Vidmar, Aleš Hladnik, Helena Gabrijelčič Tomc* University of Ljubljana Faculty of Natural Sciences and Engineering Slovenia *E-mail: [email protected] Abstract: The aim of the research was the determination of testing conditions and visual and numerical evaluation of renderings made with three different rendering engines in Maya software, which is widely used for educational and computer art purposes. In the theoretical part the overview of light phenomena and their simulation in virtual space is presented. This is followed by a detailed presentation of the main rendering methods and the results and limitations of their applications to 3D ob- jects. At the end of the theoretical part the importance of a proper testing scene and especially the role of Cornell box are explained. In the experimental part the terms and conditions as well as hardware and software used for the research are presented. This is followed by a description of the procedures, where we focused on the rendering quality and time, which enabled the comparison of settings of different render engines and determination of conditions for further rendering of testing scenes. The experimental part continued with rendering a variety of simple virtual scenes including Cornell box and virtual object with different materials and colours. Apart from visual evaluation, which was the starting point for comparison of renderings, a procedure for numerical estimation and colour deviations of ren- derings using the selected regions of interest in the final images is presented. -
Simulations and Visualisations with the VI-Suite
Simulations and Visualisations with the VI-Suite For VI-Suite Version 0.6 (document version 0.6.0.1) Dr Ryan Southall - School of Architecture & Design - University of Brighton. Contents 1 Introduction .............................................. 3 2 Installation .............................................. 3 3 Configuration ............................................. 4 4 The VI-Suite Interface ........................................ 5 4.1 Changes from v0.4 ...................................... 5 4.2 Collections .......................................... 5 4.3 File structure ......................................... 5 4.4 The Node System ....................................... 5 4.4.1 VI-Suite Nodes .................................. 6 4.4.2 EnVi Material nodes ................................ 7 4.4.3 EnVi Network nodes ................................ 7 4.5 Other panels ......................................... 8 4.5.1 Object properties panel .............................. 8 4.5.2 Material properties panel ............................. 9 4.5.3 Visualisation panel ................................. 10 4.6 Common Nodes ....................................... 11 4.6.1 The VI Location node ............................... 11 4.6.2 The ASC Import node ............................... 11 4.6.3 The VI Chart node ................................. 12 4.6.4 The VI CSV Export node ............................. 12 4.6.5 The Text Edit Node ................................ 13 4.6.6 The VI Metrics node ................................ 13 4.7 Specific