Multivariate data visualization using shadow
|
|
- Evan Wilkinson
- 8 years ago
- Views:
Transcription
1 Proceedings of the IIEEJ Ima and Visual Computing Wor Kuching, Malaysia, Novembe Multivariate data visualization using shadow Zhongxiang ZHENG Suguru SAITO Tokyo Institute of Technology ABSTRACT When visualizing data, one expected effect is to overview the data intuitively. In case of multivariate data visualization, combinations of visual cues which are color, texture, shape, size and orientation have been used. In this study, we focus on shadow which is distinguished from texture or color gradation unconsciously by human perception as a new visual cue for visualization, and introduce three methods which use shadows for multivariate data visualization. These are shadow by cylinder, texture-like shadow, and the combination of them. As the experimental result, we show visualization images that these methods make from weather data. 1 INTRODUCTION When visualizing data, one expected effect is to overview the data intuitively. Especially in case of visualizing multivariate data, it is very useful to display them at the same time. In that case, it is necessary to display the values so that viewer can read each element separately. Elements that have been used to visualize multivariate data are color, texture, shape, size and orientation. Visualization has been achieved by using these elements together[1]. In this study, we focus on the shadow which has not been used as an element for visualization. When considering the effect of the shadow, the presence of the shadow will become an important clue for the relationship of object positions, the shape of the shadow receiver s surface and the shape of the occluder[2]. In addition, we can cancel the change of color caused by the shadow as 1 we realize through some optical illusions[3]. That is, change of color by the base color change and by shadow can unconsciously be recognized separately. Therefore, We propose visualization methods that uses these characteristics of the shadow. 2 PREVIOUS WORK When using colors for multivariate data visualization, a certain color property tends to reduce readability of other properties. Rheingans showed that the difficulty of reading can be reduced by using multivariate data with the pair of hue and brightness is relatively lower than other pairs of color properties[4]. Several methods which use texture for visualization were proposed. Natural textures which are more intricate and rich in detail than standard primitives archives more vast and comprehensive data representation than standard primitives are used for multivariate data visualization[5]. To visualize multivariate data, data attributes correspond to the scale, orientation and brightness of textures respectively[6]. However, these correspondence is not intuitive to understand. In this paper, we propose the technique which is easy and intuitive to read the value like a bar graph. Colin[7] proposed the method to visualize two variables with high readability by using textures and colors together. However textures are overlapped on background colors, important information may be covered completely by these textures. We propose the visualization technique using the shadow which does not hide background colors completely.
2 3 OUR METHOD We introduce three methods which use shadows for multivariate data visualization. There are shadow by cylinder, texture-like shadow, and the combination of them. 3.1 Shadow by cylinder with bump shade The data to be displayed is 2 variate data which can be mapped on a plane. var 1 and var 2 take the values from 0 to 1. var 1 decides a color and var 2 corresponds to height. These two values generates a colored bump surface. Hereafter, the color determined by var 1 is called ground color. After performing the spline interpolation to var 2, a smooth bump surface whose height is decided by var 2 is generated. We display the local difference of the surface by shade. In order to distinguish the color changes by shade and by shadow, we use the technique based on the idea of the cold-to-warm tone[8] for shading. Shading is displayed using the tone of dark blue to bright yellow. Red to green tone is used for displaying var 1 as ground color. In order to display the absolute height at points on the surface, we put cylinders whose height and thickness are proportional to the height at the points. The heights of cylinders are displayed by casting shadows to surface. The form of a shadow is dependent on both the form of a surface which the shadow is cast on and the shape of an occluder. To get information from the length of shadows, the length of shadows should only be proportional to the height of cylinders. If the generated surface is the real bump surface, the length of shadows is not proportional to the height of cylinders under the influence of surface. To avoid this, the bump surface is expressed only by shading like bump mapping in our method. That is, the shadows which appear with cylinders are displayed as if on the flat plane. Cylinders are put randomly to avoid overlap of shadows. The actual calculation of RGB color C of a pixel is performed by the following equations with constants L, k, s, t, u, 2 C = LabtoRGB(l, a, b), (1) l = L + s shade t(1 shadow), (2) a = k(var 1 0.5), (3) b = u shade and (4) shade = l n, (5) where LabtoRGB(l, a, b) is the function which calculates RGB color from CIELAB color, shadow is the ratio of shadow, whose range is 0 to 1, and l and n are the normalized light vector and the normalized normal vector at the pixel calculated from fake bump surface. When pixel is in a shadow completely and shadow becomes 0 which is calculated by PCF[9]. 3.2 Texture-like shadow Considering with the possibility of the simultaneous use with shadow by cylinder we design one more type of shadow, texture-like shadow. To display shadow by cylinder with shading and texture-like shadow at the same time, we need to use marks which is easy to distinct and read values. We use a series of marks as shown in Fig. 1. A texture-like shadow is equal to an orthogonal projection of a occluder. Occluders whose shape varied by var 2 are set above the camera and a parallel light is put above the occluders. Size of occluders is varied so that the size of a shadow becomes the largest when var 2 = 1 and becomes smallest when var 2 = 0. Since it is guaranteed that these shadows do not overlap, these shadows can be expressed in higher density than shadows by cylinder. When displaying var 1 using color and var 2 with texture-like shadow simultaneously, equation (1), (2), and (3) are calculated with b = Combined method We consider the combination of color, shade, shadow by cylinder, and a texture-like shadow to visualize 3 variate data. When combining shadow by cylinder and a texture-like shadow, two light sources are required
3 s and t are related with the change of brightness. When s and u are large, the bumpy surface is easy to see. When t is large, shadows become dark and become easy to see. However the readability of ground color is reduced when s,u and t are too large. Figure 1: Example of texture-like shadow. Display values which change from 0 to 1 continuously. to generate two kinds of shadows. Because the densities of a shadows are different, the influence to the readability of ground colors are also difference. The distance of shadows in texture-like shadow is adjusted to be shorter than the average distance of cylinders. The darkness of texture-like shadow are adjusted to be brighter than shadow by cylinder by adjusting intensity of lights. When calculating a final color, the same calculation as Sec. 3.1 is performed under each light source condition, and the values of shade and shadow are decided by the weighted average with equations, shade = w 1shade 1 + w 2 shade 2 w 1 + w 2 and (6) shadow = w 1shadow 1 + w 2 shadow 2 w 1 + w 2 (7) where, w 1 and w 2 are the intensities of light sources and shade 1, shade 2, shadow 1 and shadow 2 are results of shade and shadow under each light source. 3.4 setting of parameters and a light sources Five coefficients L, k, s, t, u are used in these proposal techniques. L is the coefficient of the brightness of ground color, s is the coefficient of change on color axis of green to red, s is the coefficient of brightness change by shading, t is the coefficient of the decrease of brightness by a shadow and u is the coefficient of change on color axis of blue to yellow which caused by shading. Readability depends on these five coefficients. Since ground colors become dark by a shadow, L should take a large value. When k is larger, the ground color becomes more vivid. However the color will be out of the RGB color space if k is too large. Both 4 RESULTS We show results of our method applied for weather data. We set parameters as L = 70, k = 70, s = 20, t = 15, u = 20 in Fig.2(a)(b) and L = 70, k = 70, s = 20, t = 35, u = 20 in Fig.2(c). In these results, color, shade and shadow by cylinder and texture-like shadow correspond to temperature, wind speed and humidity respectively. Fig.2(a) shows temperature and wind speed. Fig.2(b) shows temperature and humidity. Fig.2(c) shows temperature, wind speed and humidity. In each case, the color element under shadows is easy to see. By combining shadow by cylinder and shade for one variate, we can see both local differences with high resolution and absolute values. Shadow by cylinder and texture-like shadow are easy to distinguish, even they are overlapped. The shade of a bump surface and the length of shadows by cylinder, visualize local change and absolute value of data respectively. Showing change of colors by shadow and shade with different color axis, we can read two types of color changes separately. Fig.3 are results of every 6 hours of weather data. We can recognize that the big wind region moves from south of Japan to middle of Japan easily. 5 CONCLUSION We proposed three visualization methods to visualize multivariate data using shadows, shade and ground color. In our methods, shadows do not hide ground colors completely and we can read both shadows and ground colors easily. To distinguish shade and shadows, these change of color is rendered with different color axes. As future work, we will perform user tests to evaluate out methods. 3
4 (a)result using color, shade and shadow by cylinder (b)result using color and texture-like shadow (c)result using color, shade, shadow by cylinder and texture-like shadow Figure 2: Example results by three methods. 4
5 Figure 3: Results which visualize weather data of every 6 hours. 5
6 References [1] H. Senay and E. Ignatius. A knowledge-based system for visualization design. Computer Graphics and Applications, IEEE, Vol. 14, No. 6, pp , nov [2] Pascal Mamassian, David C. Knill, and Daniel Kersten. The perception of cast shadows. Trends in Cognitive Sciences, Vol. 2, No. 8, pp , August [3] Edward H. Adelson. Checkershadow illusion. checkershadow_illusion.html. [4] Penny Rheingans. Task-based color scale design. In Proceedings Applied Image and Pattern Recognition. SPIE, pp , [5] Victoria Interrante. Harnessing natural textures for multivariate visualization. IEEE Comput. Graph. Appl., Vol. 20, No. 6, pp. 6 11, November [6] Ying Tang, Huamin Qu, Yingcai Wu, and Hong Zhou. Natural textures for weather data visualization. In Information Visualization, IV Tenth International Conference on, pp , july [7] Colin Ware. Quantitative texton sequences for legible bivariate maps. IEEE Transactions on Visualization and Computer Graphics, Vol. 15, pp , [8] Amy Gooch, Bruce Gooch, Peter Shirley, and Elaine Cohen. A non-photorealistic lighting model for automatic technical illustration. In Proceedings of the 25th annual conference on Computer graphics and interactive techniques, SIGGRAPH 98, pp , New York, NY, USA, ACM. [9] William T. Reeves, David H. Salesin, and Robert L. Cook. Rendering antialiased shadows with depth maps. SIGGRAPH Comput. Graph., Vol. 21, pp , August
A Short Introduction to Computer Graphics
A Short Introduction to Computer Graphics Frédo Durand MIT Laboratory for Computer Science 1 Introduction Chapter I: Basics Although computer graphics is a vast field that encompasses almost any graphical
More informationChoosing Colors for Data Visualization Maureen Stone January 17, 2006
Choosing Colors for Data Visualization Maureen Stone January 17, 2006 The problem of choosing colors for data visualization is expressed by this quote from information visualization guru Edward Tufte:
More informationExpert Color Choices for Presenting Data
Expert Color Choices for Presenting Data Maureen Stone, StoneSoup Consulting The problem of choosing colors for data visualization is expressed by this quote from information visualization guru Edward
More informationINTRODUCTION TO RENDERING TECHNIQUES
INTRODUCTION TO RENDERING TECHNIQUES 22 Mar. 212 Yanir Kleiman What is 3D Graphics? Why 3D? Draw one frame at a time Model only once X 24 frames per second Color / texture only once 15, frames for a feature
More informationVisibility optimization for data visualization: A Survey of Issues and Techniques
Visibility optimization for data visualization: A Survey of Issues and Techniques Ch Harika, Dr.Supreethi K.P Student, M.Tech, Assistant Professor College of Engineering, Jawaharlal Nehru Technological
More informationTemplate-based Eye and Mouth Detection for 3D Video Conferencing
Template-based Eye and Mouth Detection for 3D Video Conferencing Jürgen Rurainsky and Peter Eisert Fraunhofer Institute for Telecommunications - Heinrich-Hertz-Institute, Image Processing Department, Einsteinufer
More informationUsing Photorealistic RenderMan for High-Quality Direct Volume Rendering
Using Photorealistic RenderMan for High-Quality Direct Volume Rendering Cyrus Jam cjam@sdsc.edu Mike Bailey mjb@sdsc.edu San Diego Supercomputer Center University of California San Diego Abstract With
More informationVisualization and Feature Extraction, FLOW Spring School 2016 Prof. Dr. Tino Weinkauf. Flow Visualization. Image-Based Methods (integration-based)
Visualization and Feature Extraction, FLOW Spring School 2016 Prof. Dr. Tino Weinkauf Flow Visualization Image-Based Methods (integration-based) Spot Noise (Jarke van Wijk, Siggraph 1991) Flow Visualization:
More informationDATA VISUALIZATION GABRIEL PARODI STUDY MATERIAL: PRINCIPLES OF GEOGRAPHIC INFORMATION SYSTEMS AN INTRODUCTORY TEXTBOOK CHAPTER 7
DATA VISUALIZATION GABRIEL PARODI STUDY MATERIAL: PRINCIPLES OF GEOGRAPHIC INFORMATION SYSTEMS AN INTRODUCTORY TEXTBOOK CHAPTER 7 Contents GIS and maps The visualization process Visualization and strategies
More informationComputer-Generated Photorealistic Hair
Computer-Generated Photorealistic Hair Alice J. Lin Department of Computer Science, University of Kentucky, Lexington, KY 40506, USA ajlin0@cs.uky.edu Abstract This paper presents an efficient method for
More informationD animation. Advantages of 2-D2. Advantages of 3-D3. Related work. Key idea. Applications of Computer Graphics in Cel Animation.
Page 1 Applications of Computer Graphics in Cel Animation 3-D D and 2-D 2 D animation Adam Finkelstein Princeton University COS 426 Spring 2003 Homer 3-D3 Homer 2-D2 Advantages of 3-D3 Complex lighting
More informationGreen = 0,255,0 (Target Color for E.L. Gray Construction) CIELAB RGB Simulation Result for E.L. Gray Match (43,215,35) Equal Luminance Gray for Green
Red = 255,0,0 (Target Color for E.L. Gray Construction) CIELAB RGB Simulation Result for E.L. Gray Match (184,27,26) Equal Luminance Gray for Red = 255,0,0 (147,147,147) Mean of Observer Matches to Red=255
More informationRobert Collins CSE598G. More on Mean-shift. R.Collins, CSE, PSU CSE598G Spring 2006
More on Mean-shift R.Collins, CSE, PSU Spring 2006 Recall: Kernel Density Estimation Given a set of data samples x i ; i=1...n Convolve with a kernel function H to generate a smooth function f(x) Equivalent
More informationBuilding an Advanced Invariant Real-Time Human Tracking System
UDC 004.41 Building an Advanced Invariant Real-Time Human Tracking System Fayez Idris 1, Mazen Abu_Zaher 2, Rashad J. Rasras 3, and Ibrahiem M. M. El Emary 4 1 School of Informatics and Computing, German-Jordanian
More informationIntroduction to Computer Graphics
Introduction to Computer Graphics Torsten Möller TASC 8021 778-782-2215 torsten@sfu.ca www.cs.sfu.ca/~torsten Today What is computer graphics? Contents of this course Syllabus Overview of course topics
More informationComputer Applications in Textile Engineering. Computer Applications in Textile Engineering
3. Computer Graphics Sungmin Kim http://latam.jnu.ac.kr Computer Graphics Definition Introduction Research field related to the activities that includes graphics as input and output Importance Interactive
More informationPerception of Light and Color
Perception of Light and Color Theory and Practice Trichromacy Three cones types in retina a b G+B +R Cone sensitivity functions 100 80 60 40 20 400 500 600 700 Wavelength (nm) Short wavelength sensitive
More informationVisualization methods for patent data
Visualization methods for patent data Treparel 2013 Dr. Anton Heijs (CTO & Founder) Delft, The Netherlands Introduction Treparel can provide advanced visualizations for patent data. This document describes
More informationFour-dimensional Mathematical Data Visualization via Embodied Four-dimensional Space Display System
Original Paper Forma, 26, 11 18, 2011 Four-dimensional Mathematical Data Visualization via Embodied Four-dimensional Space Display System Yukihito Sakai 1,2 and Shuji Hashimoto 3 1 Faculty of Information
More informationVISUALIZATION TOOLS FOR AGENT-BASED MODELING IN NETLOGO
1 VISUALIZATION TOOLS FOR AGENT-BASED MODELING IN NETLOGO D. KORNHAUSER,* Northwestern University, IL W. RAND, Northwestern University, IL U. WILENSKY, Northwestern University, IL ABSTRACT In the field
More informationTutorial 3: Graphics and Exploratory Data Analysis in R Jason Pienaar and Tom Miller
Tutorial 3: Graphics and Exploratory Data Analysis in R Jason Pienaar and Tom Miller Getting to know the data An important first step before performing any kind of statistical analysis is to familiarize
More informationElements of Art Name Design Project!
Elements of Art Name Design Project! 1. On the Project paper Lightly & Largely sketch out the Hollow letters of your first name. 2. Then Outline in Shaprie. 3. Divide your space into 7 sections (any way
More informationVISUAL ARTS VOCABULARY
VISUAL ARTS VOCABULARY Abstract Artwork in which the subject matter is stated in a brief, simplified manner; little or no attempt is made to represent images realistically, and objects are often simplified
More informationEnhanced LIC Pencil Filter
Enhanced LIC Pencil Filter Shigefumi Yamamoto, Xiaoyang Mao, Kenji Tanii, Atsumi Imamiya University of Yamanashi {daisy@media.yamanashi.ac.jp, mao@media.yamanashi.ac.jp, imamiya@media.yamanashi.ac.jp}
More informationPrinciples of Data Visualization for Exploratory Data Analysis. Renee M. P. Teate. SYS 6023 Cognitive Systems Engineering April 28, 2015
Principles of Data Visualization for Exploratory Data Analysis Renee M. P. Teate SYS 6023 Cognitive Systems Engineering April 28, 2015 Introduction Exploratory Data Analysis (EDA) is the phase of analysis
More informationIntuitive Navigation in an Enormous Virtual Environment
/ International Conference on Artificial Reality and Tele-Existence 98 Intuitive Navigation in an Enormous Virtual Environment Yoshifumi Kitamura Shinji Fukatsu Toshihiro Masaki Fumio Kishino Graduate
More informationImage Processing and Computer Graphics. Rendering Pipeline. Matthias Teschner. Computer Science Department University of Freiburg
Image Processing and Computer Graphics Rendering Pipeline Matthias Teschner Computer Science Department University of Freiburg Outline introduction rendering pipeline vertex processing primitive processing
More informationCS171 Visualization. The Visualization Alphabet: Marks and Channels. Alexander Lex alex@seas.harvard.edu. [xkcd]
CS171 Visualization Alexander Lex alex@seas.harvard.edu The Visualization Alphabet: Marks and Channels [xkcd] This Week Thursday: Task Abstraction, Validation Homework 1 due on Friday! Any more problems
More information3 hours One paper 70 Marks. Areas of Learning Theory
GRAPHIC DESIGN CODE NO. 071 Class XII DESIGN OF THE QUESTION PAPER 3 hours One paper 70 Marks Section-wise Weightage of the Theory Areas of Learning Theory Section A (Reader) Section B Application of Design
More informationHow many PIXELS do you need? by ron gibbs
How many PIXELS do you need? by ron gibbs We continue to move forward into the age of digital photography. The basic building block of digital images is the PIXEL which is the shorthand for picture element.
More informationVisualizing Network Relationships
Visualizing Network Relationships Scott Murray Abstract The vast majority of network visualizations are based on simple graphs and are rendered with connecting lines that communicate only one binary value:
More informationA Scientific Visualization Schema Incorporating Perceptual Concepts
A Scientific Visualization Schema Incorporating Perceptual Concepts Burkhard Wünsche and Richard Lobb Department of Computer Science The University of Auckland, Private Bag 92019 Auckland, New Zealand
More informationHSI BASED COLOUR IMAGE EQUALIZATION USING ITERATIVE n th ROOT AND n th POWER
HSI BASED COLOUR IMAGE EQUALIZATION USING ITERATIVE n th ROOT AND n th POWER Gholamreza Anbarjafari icv Group, IMS Lab, Institute of Technology, University of Tartu, Tartu 50411, Estonia sjafari@ut.ee
More informationBernice E. Rogowitz and Holly E. Rushmeier IBM TJ Watson Research Center, P.O. Box 704, Yorktown Heights, NY USA
Are Image Quality Metrics Adequate to Evaluate the Quality of Geometric Objects? Bernice E. Rogowitz and Holly E. Rushmeier IBM TJ Watson Research Center, P.O. Box 704, Yorktown Heights, NY USA ABSTRACT
More informationRobot Perception Continued
Robot Perception Continued 1 Visual Perception Visual Odometry Reconstruction Recognition CS 685 11 Range Sensing strategies Active range sensors Ultrasound Laser range sensor Slides adopted from Siegwart
More informationAdding Animation With Cinema 4D XL
Step-by-Step Adding Animation With Cinema 4D XL This Step-by-Step Card covers the basics of using the animation features of Cinema 4D XL. Note: Before you start this Step-by-Step Card, you need to have
More informationCollaborative Data Analysis on Wall Displays
Collaborative Data Analysis on Wall Displays Challenges for Visualization Petra Isenberg (petra.isenberg@inria.fr) Anastasia Bezerianos (anastasia.bezerianos@lri.fr) 2 [source: The Diverse and Exploding
More informationDATA LAYOUT AND LEVEL-OF-DETAIL CONTROL FOR FLOOD DATA VISUALIZATION
DATA LAYOUT AND LEVEL-OF-DETAIL CONTROL FOR FLOOD DATA VISUALIZATION Sayaka Yagi Takayuki Itoh Ochanomizu University Mayumi Kurokawa Yuuichi Izu Takahisa Yoneyama Takashi Kohara Toshiba Corporation ABSTRACT
More informationDiagrams and Graphs of Statistical Data
Diagrams and Graphs of Statistical Data One of the most effective and interesting alternative way in which a statistical data may be presented is through diagrams and graphs. There are several ways in
More informationGraphic Design. Background: The part of an artwork that appears to be farthest from the viewer, or in the distance of the scene.
Graphic Design Active Layer- When you create multi layers for your images the active layer, or the only one that will be affected by your actions, is the one with a blue background in your layers palette.
More informationDigital Image Basics. Introduction. Pixels and Bitmaps. Written by Jonathan Sachs Copyright 1996-1999 Digital Light & Color
Written by Jonathan Sachs Copyright 1996-1999 Digital Light & Color Introduction When using digital equipment to capture, store, modify and view photographic images, they must first be converted to a set
More informationLecture 1: The Visual System
ITS 102: Visualize This! Lecture 1: The Visual System Klaus Mueller Computer Science Department Stony Brook University The Visual Brain Over 50% of the human brain is dedicated to vision and visual representations,
More informationColorado School of Mines Computer Vision Professor William Hoff
Professor William Hoff Dept of Electrical Engineering &Computer Science http://inside.mines.edu/~whoff/ 1 Introduction to 2 What is? A process that produces from images of the external world a description
More informationVision based Vehicle Tracking using a high angle camera
Vision based Vehicle Tracking using a high angle camera Raúl Ignacio Ramos García Dule Shu gramos@clemson.edu dshu@clemson.edu Abstract A vehicle tracking and grouping algorithm is presented in this work
More informationBig Data: Rethinking Text Visualization
Big Data: Rethinking Text Visualization Dr. Anton Heijs anton.heijs@treparel.com Treparel April 8, 2013 Abstract In this white paper we discuss text visualization approaches and how these are important
More informationDigitisation Disposal Policy Toolkit
Digitisation Disposal Policy Toolkit Glossary of Digitisation Terms August 2014 Department of Science, Information Technology, Innovation and the Arts Document details Security Classification Date of review
More informationPart 2: Data Visualization How to communicate complex ideas with simple, efficient and accurate data graphics
Part 2: Data Visualization How to communicate complex ideas with simple, efficient and accurate data graphics Why visualize data? The human eye is extremely sensitive to differences in: Pattern Colors
More informationCartoon-Looking Rendering of 3D-Scenes
Cartoon-Looking Rendering of 3D-Scenes Philippe Decaudin 1 Research Report INRIA #2919 June 1996 Abstract We present a rendering algorithm that produces images with the appearance of a traditional cartoon
More information3D Data Visualization / Casey Reas
3D Data Visualization / Casey Reas Large scale data visualization offers the ability to see many data points at once. By providing more of the raw data for the viewer to consume, visualization hopes to
More informationPrinciples of Data Visualization
Principles of Data Visualization by James Bernhard Spring 2012 We begin with some basic ideas about data visualization from Edward Tufte (The Visual Display of Quantitative Information (2nd ed.)) He gives
More informationMonash University Clayton s School of Information Technology CSE3313 Computer Graphics Sample Exam Questions 2007
Monash University Clayton s School of Information Technology CSE3313 Computer Graphics Questions 2007 INSTRUCTIONS: Answer all questions. Spend approximately 1 minute per mark. Question 1 30 Marks Total
More informationSection 11.4: Equations of Lines and Planes
Section 11.4: Equations of Lines and Planes Definition: The line containing the point ( 0, 0, 0 ) and parallel to the vector v = A, B, C has parametric equations = 0 + At, = 0 + Bt, = 0 + Ct, where t R
More informationDigital Image Fundamentals. Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr
Digital Image Fundamentals Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr Imaging process Light reaches surfaces in 3D. Surfaces reflect. Sensor element receives
More informationA Proposal for OpenEXR Color Management
A Proposal for OpenEXR Color Management Florian Kainz, Industrial Light & Magic Revision 5, 08/05/2004 Abstract We propose a practical color management scheme for the OpenEXR image file format as used
More information35% Oversight Failure to. Detect 22% 35% STUDY OF FACE DESIGN, LIGHTING SYSTEM DESIGN FOR ENHANCED DETECTION RATE OF MOTORCYCLES
STUDY OF FACE DESIGN, LIGHTING SYSTEM DESIGN FOR ENHANCED DETECTION RATE OF MOTORCYCLES Kazuyuki, Maruyama Yojiro, Tsutsumi Motorcycle R&D Center/Honda R&D Co., Ltd. Japan Yutaka, Murata Future Transportation
More informationTime Series Data Visualization
Time Series Data Visualization Time Series Data Fundamental chronological component to the data set Random sample of 4000 graphics from 15 of world s newspapers and magazines from 74-80 found that 75%
More informationProjection Center Calibration for a Co-located Projector Camera System
Projection Center Calibration for a Co-located Camera System Toshiyuki Amano Department of Computer and Communication Science Faculty of Systems Engineering, Wakayama University Sakaedani 930, Wakayama,
More informationVisualizing of Berkeley Earth, NASA GISS, and Hadley CRU averaging techniques
Visualizing of Berkeley Earth, NASA GISS, and Hadley CRU averaging techniques Robert Rohde Lead Scientist, Berkeley Earth Surface Temperature 1/15/2013 Abstract This document will provide a simple illustration
More informationA Color Placement Support System for Visualization Designs Based on Subjective Color Balance
A Color Placement Support System for Visualization Designs Based on Subjective Color Balance Eric Cooper and Katsuari Kamei College of Information Science and Engineering Ritsumeikan University Abstract:
More informationComputer Animation: Art, Science and Criticism
Computer Animation: Art, Science and Criticism Tom Ellman Harry Roseman Lecture 12 Ambient Light Emits two types of light: Directional light, coming from a single point Contributes to diffuse shading.
More informationLines & Planes. Packages: linalg, plots. Commands: evalm, spacecurve, plot3d, display, solve, implicitplot, dotprod, seq, implicitplot3d.
Lines & Planes Introduction and Goals: This lab is simply to give you some practice with plotting straight lines and planes and how to do some basic problem solving with them. So the exercises will be
More informationVisualization Techniques in Data Mining
Tecniche di Apprendimento Automatico per Applicazioni di Data Mining Visualization Techniques in Data Mining Prof. Pier Luca Lanzi Laurea in Ingegneria Informatica Politecnico di Milano Polo di Milano
More informationTEXTURE AND BUMP MAPPING
Department of Applied Mathematics and Computational Sciences University of Cantabria UC-CAGD Group COMPUTER-AIDED GEOMETRIC DESIGN AND COMPUTER GRAPHICS: TEXTURE AND BUMP MAPPING Andrés Iglesias e-mail:
More informationVisualization. For Novices. ( Ted Hall ) University of Michigan 3D Lab Digital Media Commons, Library http://um3d.dc.umich.edu
Visualization For Novices ( Ted Hall ) University of Michigan 3D Lab Digital Media Commons, Library http://um3d.dc.umich.edu Data Visualization Data visualization deals with communicating information about
More informationCourse Overview. CSCI 480 Computer Graphics Lecture 1. Administrative Issues Modeling Animation Rendering OpenGL Programming [Angel Ch.
CSCI 480 Computer Graphics Lecture 1 Course Overview January 14, 2013 Jernej Barbic University of Southern California http://www-bcf.usc.edu/~jbarbic/cs480-s13/ Administrative Issues Modeling Animation
More informationAUDIO. 1. An audio signal is an representation of a sound. a. Acoustical b. Environmental c. Aesthetic d. Electrical
Essentials of the AV Industry Pretest Not sure if you need to take Essentials? Do you think you know the basics of Audio Visual? Take this quick assessment test on Audio, Visual, and Systems to find out!
More informationCOMP175: Computer Graphics. Lecture 1 Introduction and Display Technologies
COMP175: Computer Graphics Lecture 1 Introduction and Display Technologies Course mechanics Number: COMP 175-01, Fall 2009 Meetings: TR 1:30-2:45pm Instructor: Sara Su (sarasu@cs.tufts.edu) TA: Matt Menke
More informationA NEW SUPER RESOLUTION TECHNIQUE FOR RANGE DATA. Valeria Garro, Pietro Zanuttigh, Guido M. Cortelazzo. University of Padova, Italy
A NEW SUPER RESOLUTION TECHNIQUE FOR RANGE DATA Valeria Garro, Pietro Zanuttigh, Guido M. Cortelazzo University of Padova, Italy ABSTRACT Current Time-of-Flight matrix sensors allow for the acquisition
More informationMulti-Attribute Glyphs on Venn and Euler Diagrams to Represent Data and Aid Visual Decoding
Multi-Attribute Glyphs on Venn and Euler Diagrams to Represent Data and Aid Visual Decoding Richard Brath Oculus Info Inc., Toronto, ON, Canada richard.brath@oculusinfo.com Abstract. Representing quantities
More informationUsing Microsoft Picture Manager
Using Microsoft Picture Manager Storing Your Photos It is suggested that a county store all photos for use in the County CMS program in the same folder for easy access. For the County CMS Web Project it
More informationOutline. Quantizing Intensities. Achromatic Light. Optical Illusion. Quantizing Intensities. CS 430/585 Computer Graphics I
CS 430/585 Computer Graphics I Week 8, Lecture 15 Outline Light Physical Properties of Light and Color Eye Mechanism for Color Systems to Define Light and Color David Breen, William Regli and Maxim Peysakhov
More informationModelling 3D Avatar for Virtual Try on
Modelling 3D Avatar for Virtual Try on NADIA MAGNENAT THALMANN DIRECTOR MIRALAB UNIVERSITY OF GENEVA DIRECTOR INSTITUTE FOR MEDIA INNOVATION, NTU, SINGAPORE WWW.MIRALAB.CH/ Creating Digital Humans Vertex
More informationAutomatic 3D Reconstruction via Object Detection and 3D Transformable Model Matching CS 269 Class Project Report
Automatic 3D Reconstruction via Object Detection and 3D Transformable Model Matching CS 69 Class Project Report Junhua Mao and Lunbo Xu University of California, Los Angeles mjhustc@ucla.edu and lunbo
More informationCreating a History Day Exhibit Adapted from materials at the National History Day website
Creating a History Day Exhibit Adapted from materials at the National History Day website Exhibits are designed to display visual and written information on topics in an attractive and understandable manner.
More informationELEMENTS AND PRINCIPLES OF DESIGN
APPENDIX A1 4 T T ELEMENTS AND PRINCIPLES OF DESIGN Groups: 1. Select an advertisement. 2. Examine the advertisement to find examples of a few elements and principles of design that you are familiar with.
More informationMcAFEE IDENTITY. October 2011
McAFEE IDENTITY 4.2 Our logo is one of our most valuable assets. To ensure that it remains a strong representation of our company, we must present it in a consistent and careful manner across all channels
More informationPART 1 Basic Setup. Section 1.1 Direct The Strokes 1.1.1
Animated Impressionism with Adobe After Effects This tutorial covers a technique for animating paint strokes applied to a still image so that it appears to be a work of impressionistic art. Adobe After
More informationInvestigation of Color Aliasing of High Spatial Frequencies and Edges for Bayer-Pattern Sensors and Foveon X3 Direct Image Sensors
Investigation of Color Aliasing of High Spatial Frequencies and Edges for Bayer-Pattern Sensors and Foveon X3 Direct Image Sensors Rudolph J. Guttosch Foveon, Inc. Santa Clara, CA Abstract The reproduction
More informationColor holographic 3D display unit with aperture field division
Color holographic 3D display unit with aperture field division Weronika Zaperty, Tomasz Kozacki, Malgorzata Kujawinska, Grzegorz Finke Photonics Engineering Division, Faculty of Mechatronics Warsaw University
More informationTHIS paper investigates the problem of visualizing multivariate. Large Datasets at a Glance: Combining Textures and Colors in Scientific Visualization
Large Datasets at a Glance: Combining Textures and Colors in Scientific Visualization Christopher G. Healey and James T. Enns Abstract This paper presents a new method for using texture and color to visualize
More informationOp Art: Working With Optical Illusions Review Questions
Op Art: Working With Optical Illusions Review Questions Name Period Date Answer the following questions in complete sentences. PAGES 2-3 1. How did Op art reflect 1960s culture? a. The 1960s were a time
More informationAn Energy-Based Vehicle Tracking System using Principal Component Analysis and Unsupervised ART Network
Proceedings of the 8th WSEAS Int. Conf. on ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING & DATA BASES (AIKED '9) ISSN: 179-519 435 ISBN: 978-96-474-51-2 An Energy-Based Vehicle Tracking System using Principal
More informationThe 3D rendering pipeline (our version for this class)
The 3D rendering pipeline (our version for this class) 3D models in model coordinates 3D models in world coordinates 2D Polygons in camera coordinates Pixels in image coordinates Scene graph Camera Rasterization
More informationMassArt Studio Foundation: Visual Language Digital Media Cookbook, Fall 2013
INPUT OUTPUT 08 / IMAGE QUALITY & VIEWING In this section we will cover common image file formats you are likely to come across and examine image quality in terms of resolution and bit depth. We will cover
More informationLogo Standards Guideline
Logo Standards Guideline TABLE OF CONTENTS Nurturing The Brand 1 Logo Guidelines 2 Correct Usage 2 Color Guidelines 6 How to Use the Provided Logo Files 9 Glossary 10 NURTURING THE BRAND THE FOLLOWING
More informationToday s Class. High Dimensional Data & Dimensionality Reduc9on. Readings from Last Week: Readings from Last Week: Scien9fic Data.
High Dimensional Data & Dimensionality Reduc9on Readings from Last Week: Readings from Last Week: QSplat: A Mul9resolu9on Point Rendering System for Large Meshes, Rusinkiewicz & Levoy, SIGGRAPH 2000 Tree
More informationOptical Design Tools for Backlight Displays
Optical Design Tools for Backlight Displays Introduction Backlights are used for compact, portable, electronic devices with flat panel Liquid Crystal Displays (LCDs) that require illumination from behind.
More informationELEMENTS OF ART & PRINCIPLES OF DESIGN
ELEMENTS OF ART & PRINCIPLES OF DESIGN Elements of Art: 1. COLOR Color (hue) is one of the elements of art. Artists use color in many different ways. The colors we see are light waves absorbed or reflected
More informationVisualization Techniques for Geospatial Data IDV 2015/2016
Interactive Data Visualization 07 Visualization Techniques for Geospatial Data IDV 2015/2016 Notice n Author t João Moura Pires (jmp@fct.unl.pt) n This material can be freely used for personal or academic
More informationUSING ADOBE PhotoShop TO MEASURE EarthKAM IMAGES
USING ADOBE PhotoShop TO MEASURE EarthKAM IMAGES By James H. Nicholson and Ellen Vaughan Charleston County School District CAN DO Project for the EarthKAM Teacher Training Institute Introduction EarthKAM
More informationTEXT-FILLED STACKED AREA GRAPHS Martin Kraus
Martin Kraus Text can add a significant amount of detail and value to an information visualization. In particular, it can integrate more of the data that a visualization is based on, and it can also integrate
More informationVisualization Software
Visualization Software Maneesh Agrawala CS 294-10: Visualization Fall 2007 Assignment 1b: Deconstruction & Redesign Due before class on Sep 12, 2007 1 Assignment 2: Creating Visualizations Use existing
More informationAssessment. Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall
Automatic Photo Quality Assessment Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall Estimating i the photorealism of images: Distinguishing i i paintings from photographs h Florin
More informationDeferred Shading & Screen Space Effects
Deferred Shading & Screen Space Effects State of the Art Rendering Techniques used in the 3D Games Industry Sebastian Lehmann 11. Februar 2014 FREESTYLE PROJECT GRAPHICS PROGRAMMING LAB CHAIR OF COMPUTER
More informationCircle Object Recognition Based on Monocular Vision for Home Security Robot
Journal of Applied Science and Engineering, Vol. 16, No. 3, pp. 261 268 (2013) DOI: 10.6180/jase.2013.16.3.05 Circle Object Recognition Based on Monocular Vision for Home Security Robot Shih-An Li, Ching-Chang
More informationEUSIPCO 2013 1569746737
EUSIPCO 2013 1569746737 HUE CORRECTION IN HDR TONE MAPPING Michal Seeman, Pavel Zemčík, Bronislav Přibyl Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic ABSTRACT
More informationComputer Graphics Global Illumination (2): Monte-Carlo Ray Tracing and Photon Mapping. Lecture 15 Taku Komura
Computer Graphics Global Illumination (2): Monte-Carlo Ray Tracing and Photon Mapping Lecture 15 Taku Komura In the previous lectures We did ray tracing and radiosity Ray tracing is good to render specular
More informationMULTI-LAYER VISUALIZATION OF MOBILE MAPPING DATA
MULTI-LAYER VISUALIZATION OF MOBILE MAPPING DATA D. Eggert, M. Sester Institute of Cartography and Geoinformatics, Leibniz Universität Hannover, Germany - (eggert, sester)@ikg.uni-hannover.de KEY WORDS:
More informationComputer Graphics. Introduction. Computer graphics. What is computer graphics? Yung-Yu Chuang
Introduction Computer Graphics Instructor: Yung-Yu Chuang ( 莊 永 裕 ) E-mail: c@csie.ntu.edu.tw Office: CSIE 527 Grading: a MatchMove project Computer Science ce & Information o Technolog og Yung-Yu Chuang
More information