CHAPTER 8 Multiview Drawings 377 Media
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
CHAPTER 6 PICTORIAL SKETCHING 6-1Four Types of Projections
CHAPTER 6 PICTORIAL SKETCHING 6-1Four Types of Projections Types of Projections 6-2 Axonometric Projection As shown in figure below, axonometric projections are classified as isometric projection (all axes equally foreshortened), dimetric projection (two axes equally shortened), and trimetric projection (all three axes foreshortened differently, requiring different scales for each axis). (cont) Figures below show the contrast between an isometric sketch (i.e., drawing) and an isometric projection. The isometric projection is about 25% larger than the isometric projection, but the pictorial value is obviously the same. When you create isometric sketches, you do not always have to make accurate measurements locating each point in the sketch exactly. Instead, keep your sketch in proportion. Isometric pictorials are great for showing piping layouts and structural designs. Step by Step 6.1. Isometric Sketching 6-4 Normal and Inclined Surfaces in Isometric View Making an isometric sketch of an object having normal surfaces is shown in figure below. Notice that all measurements are made parallel to the main edges of the enclosing box – that is, parallel to the isometric axes. (cont) Making an isometric sketch of an object that has inclined surfaces (and oblique edges) is shown below. Notice that inclined surfaces are located by offset, or coordinate measurements along the isometric lines. For example, distances E and F are used to locate the inclined surface M, and distances A and B are used to locate surface N. 6-5 Oblique Surfaces in Isometric View Oblique surfaces in isometric view may be drawn by finding the intersections of the oblique surfaces with isometric planes. -
Realistic Modeling and Rendering of Plant Ecosystems
Realistic modeling and rendering of plant ecosystems Oliver Deussen1 Pat Hanrahan2 Bernd Lintermann3 RadomÂõr MechÏ 4 Matt Pharr2 Przemyslaw Prusinkiewicz4 1 Otto-von-Guericke University of Magdeburg 2 Stanford University 3 The ZKM Center for Art and Media Karlsruhe 4 The University of Calgary Abstract grasslands, human-made environments, for instance parks and gar- dens, and intermediate environments, such as lands recolonized by Modeling and rendering of natural scenes with thousands of plants vegetation after forest ®res or logging. Models of these ecosystems poses a number of problems. The terrain must be modeled and plants have a wide range of existing and potential applications, including must be distributed throughout it in a realistic manner, re¯ecting the computer-assisted landscape and garden design, prediction and vi- interactions of plants with each other and with their environment. sualization of the effects of logging on the landscape, visualization Geometric models of individual plants, consistent with their po- of models of ecosystems for research and educational purposes, sitions within the ecosystem, must be synthesized to populate the and synthesis of scenes for computer animations, drive and ¯ight scene. The scene, which may consist of billions of primitives, must simulators, games, and computer art. be rendered ef®ciently while incorporating the subtleties of lighting Beautiful images of forests and meadows were created as early in a natural environment. as 1985 by Reeves and Blau [50] and featured in the computer We have developed a system built around a pipeline of tools that animation The Adventures of Andre and Wally B. [34]. Reeves and address these tasks. -
CS 543: Computer Graphics Lecture 7 (Part I): Projection Emmanuel
CS 543: Computer Graphics Lecture 7 (Part I): Projection Emmanuel Agu 3D Viewing and View Volume n Recall: 3D viewing set up Projection Transformation n View volume can have different shapes (different looks) n Different types of projection: parallel, perspective, orthographic, etc n Important to control n Projection type: perspective or orthographic, etc. n Field of view and image aspect ratio n Near and far clipping planes Perspective Projection n Similar to real world n Characterized by object foreshortening n Objects appear larger if they are closer to camera n Need: n Projection center n Projection plane n Projection: Connecting the object to the projection center camera projection plane Projection? Projectors Object in 3 space Projected image VRP COP Orthographic Projection n No foreshortening effect – distance from camera does not matter n The projection center is at infinite n Projection calculation – just drop z coordinates Field of View n Determine how much of the world is taken into the picture n Larger field of view = smaller object projection size center of projection field of view (view angle) y y z q z x Near and Far Clipping Planes n Only objects between near and far planes are drawn n Near plane + far plane + field of view = Viewing Frustum Near plane Far plane y z x Viewing Frustrum n 3D counterpart of 2D world clip window n Objects outside the frustum are clipped Near plane Far plane y z x Viewing Frustum Projection Transformation n In OpenGL: n Set the matrix mode to GL_PROJECTION n Perspective projection: use • gluPerspective(fovy, -
An Analytical Introduction to Descriptive Geometry
An analytical introduction to Descriptive Geometry Adrian B. Biran, Technion { Faculty of Mechanical Engineering Ruben Lopez-Pulido, CEHINAV, Polytechnic University of Madrid, Model Basin, and Spanish Association of Naval Architects Avraham Banai Technion { Faculty of Mathematics Prepared for Elsevier (Butterworth-Heinemann), Oxford, UK Samples - August 2005 Contents Preface x 1 Geometric constructions 1 1.1 Introduction . 2 1.2 Drawing instruments . 2 1.3 A few geometric constructions . 2 1.3.1 Drawing parallels . 2 1.3.2 Dividing a segment into two . 2 1.3.3 Bisecting an angle . 2 1.3.4 Raising a perpendicular on a given segment . 2 1.3.5 Drawing a triangle given its three sides . 2 1.4 The intersection of two lines . 2 1.4.1 Introduction . 2 1.4.2 Examples from practice . 2 1.4.3 Situations to avoid . 2 1.5 Manual drawing and computer-aided drawing . 2 i ii CONTENTS 1.6 Exercises . 2 Notations 1 2 Introduction 3 2.1 How we see an object . 3 2.2 Central projection . 4 2.2.1 De¯nition . 4 2.2.2 Properties . 5 2.2.3 Vanishing points . 17 2.2.4 Conclusions . 20 2.3 Parallel projection . 23 2.3.1 De¯nition . 23 2.3.2 A few properties . 24 2.3.3 The concept of scale . 25 2.4 Orthographic projection . 27 2.4.1 De¯nition . 27 2.4.2 The projection of a right angle . 28 2.5 The two-sheet method of Monge . 36 2.6 Summary . 39 2.7 Examples . 43 2.8 Exercises . -
Viewing in 3D
Viewing in 3D Viewing in 3D Foley & Van Dam, Chapter 6 • Transformation Pipeline • Viewing Plane • Viewing Coordinate System • Projections • Orthographic • Perspective OpenGL Transformation Pipeline Viewing Coordinate System Homogeneous coordinates in World System zw world yw ModelViewModelView Matrix Matrix xw Tractor Viewing System Viewer Coordinates System ProjectionProjection Matrix Matrix Clip y Coordinates v Front- xv ClippingClipping Wheel System P0 zv ViewportViewport Transformation Transformation ne pla ing Window Coordinates View Specifying the Viewing Coordinates Specifying the Viewing Coordinates • Viewing Coordinates system, [xv, yv, zv], describes 3D objects with respect to a viewer zw y v P v xv •A viewing plane (projection plane) is set up N P0 zv perpendicular to zv and aligned with (xv,yv) yw xw ne pla ing • In order to specify a viewing plane we have View to specify: •P0=(x0,y0,z0) is the point where a camera is located •a vector N normal to the plane • P is a point to look-at •N=(P-P)/|P -P| is the view-plane normal vector •a viewing-up vector V 0 0 •V=zw is the view up vector, whose projection onto • a point on the viewing plane the view-plane is directed up Viewing Coordinate System Projections V u N z N ; x ; y z u x • Viewing 3D objects on a 2D display requires a v v V u N v v v mapping from 3D to 2D • The transformation M, from world-coordinate into viewing-coordinates is: • A projection is formed by the intersection of certain lines (projectors) with the view plane 1 2 3 ª x v x v x v 0 º ª 1 0 0 x 0 º « » « -
Technical Drawing School of Art, Design and Architecture Sarah Adeel | Nust – Spring 2011 the Ability to ’Document Imagination’
technical drawing school of art, design and architecture sarah adeel | nust – spring 2011 the ability to ’document imagination’. a mean to design reasoning spring 2011 perspective drawings technical drawing - perspective What is perspective drawing? Perspective originally comes from Latin word per meaning “through” and specere which means “to look.” These are combined to mean “to look through” or “to look at.” Intro to technical drawing perspective technical drawing - perspective What is perspective drawing? The “art definition” of perspective specifically describes creating the appearance of distance into our art. With time, the most typical “art definition” of perspective has evolved into “the technique of representing a three-dimensional image on a two-dimensional Intro to technical drawing surface.” perspective technical drawing - perspective What is perspective drawing? Perspective is about establishing “an eye” in art through which the audience sees. By introducing a sense of depth, space and an extension of reality into art is created, enhancing audience’s participation with it. When things appear more real, they become real to the senses. Intro to technical drawing perspective technical drawing - perspective What are the ingredients of perspective drawing? Any form consists of only three basic things: • it has size or amount • it covers distance • it extends in different directions Intro to technical drawing perspective technical drawing - perspective Everyday examples of perspective drawing Photography is an example of perspectives. In photos scenes are captured having depth, height and distance. Intro to technical drawing perspective technical drawing - perspective What is linear perspective drawing? Linear Perspective: Based on the way the human eye sees the world. -
Implementation of Projections
CS488 Implementation of projections Luc RENAMBOT 1 3D Graphics • Convert a set of polygons in a 3D world into an image on a 2D screen • After theoretical view • Implementation 2 Transformations P(X,Y,Z) 3D Object Coordinates Modeling Transformation 3D World Coordinates Viewing Transformation 3D Camera Coordinates Projection Transformation 2D Screen Coordinates Window-to-Viewport Transformation 2D Image Coordinates P’(X’,Y’) 3 3D Rendering Pipeline 3D Geometric Primitives Modeling Transform into 3D world coordinate system Transformation Lighting Illuminate according to lighting and reflectance Viewing Transform into 3D camera coordinate system Transformation Projection Transform into 2D camera coordinate system Transformation Clipping Clip primitives outside camera’s view Scan Draw pixels (including texturing, hidden surface, etc.) Conversion Image 4 Orthographic Projection 5 Perspective Projection B F 6 Viewing Reference Coordinate system 7 Projection Reference Point Projection Reference Point (PRP) Center of Window (CW) View Reference Point (VRP) View-Plane Normal (VPN) 8 Implementation • Lots of Matrices • Orthographic matrix • Perspective matrix • 3D World → Normalize to the canonical view volume → Clip against canonical view volume → Project onto projection plane → Translate into viewport 9 Canonical View Volumes • Used because easy to clip against and calculate intersections • Strategies: convert view volumes into “easy” canonical view volumes • Transformations called Npar and Nper 10 Parallel Canonical Volume X or Y Defined by 6 planes -
Understanding Projection Systems
Understanding Projection Systems Understanding Projection Systems A Point: A point has no dimensions, a theoretical location that has neither length, width nor height. A point shows an exact location in space. It is important to understand that a point is not an object, but a position. We represent a point by placing a dot with a pencil. A Line: A line is a geometric object that has length and direction but no thickness. A line may be straight or curved. A line may be infinitely long. If a line has a definite length it is called a line segment or curve segment. A straight line is the shortest distance between two points which is known as the true length of the line. A line is named using letters to indicate its endpoints. B B A A AB - Straight Line Segment AB – Curved Line Segment A line may be seen as the locus of a point as it travels between two points. A B A line can graphically represent the intersection of two surfaces, the edge view of a surface, or the limiting element of a surface. B A Plane: A plane is a flat surface which is infinitely large with zero thickness. Just as a point generates a line, a line can generate a plane. A A portion of a plane is referred to as a lamina. A Plane may be defined in a number of different ways. - 1 - Understanding Projection Systems A plane may be defined by; (i) 3 non-linear points (ii) A line and a point (iii) Two intersecting lines (iv) Two Parallel Lines (The point can not lie on the line) Descriptive Geometry: refers to the representation of 3D objects in a 2D format using points, lines and planes. -
Visualization in Multiobjective Optimization
Final version Visualization in Multiobjective Optimization Bogdan Filipič Tea Tušar Tutorial slides are available at CEC Tutorial, Donostia - San Sebastián, June 5, 2017 http://dis.ijs.si/tea/research.htm Computational Intelligence Group Department of Intelligent Systems Jožef Stefan Institute Ljubljana, Slovenia 2 Contents Introduction A taxonomy of visualization methods Visualizing single approximation sets Introduction Visualizing repeated approximation sets Summary References 3 Introduction Introduction Multiobjective optimization problem Visualization in multiobjective optimization Minimize Useful for different purposes [14] f: X ! F • Analysis of solutions and solution sets f:(x ;:::; x ) 7! (f (x ;:::; x );:::; f (x ;:::; x )) 1 n 1 1 n m 1 n • Decision support in interactive optimization • Analysis of algorithm performance • X is an n-dimensional decision space ⊆ Rm ≥ • F is an m-dimensional objective space (m 2) Visualizing solution sets in the decision space • Problem-specific ! Conflicting objectives a set of optimal solutions • If X ⊆ Rm, any method for visualizing multidimensional • Pareto set in the decision space solutions can be used • Pareto front in the objective space • Not the focus of this tutorial 4 5 Introduction Introduction Visualization can be hard even in 2-D Stochastic optimization algorithms Visualizing solution sets in the objective space • Single run ! single approximation set • Interested in sets of mutually nondominated solutions called ! approximation sets • Multiple runs multiple approximation sets • Different -
Orthographic and Perspective Projection—Part 1 Drawing As
I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S From 3D to 2D: Orthographic and Perspective Projection—Part 1 •History • Geometrical Constructions 3D Viewing I • Types of Projection • Projection in Computer Graphics Andries van Dam September 15, 2005 3D Viewing I Andries van Dam September 15, 2005 3D Viewing I 1/38 I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S Drawing as Projection Early Examples of Projection • Plan view (orthographic projection) from Mesopotamia, 2150 BC: earliest known technical • Painting based on mythical tale as told by Pliny the drawing in existence Elder: Corinthian man traces shadow of departing lover Carlbom Fig. 1-1 • Greek vases from late 6th century BC show perspective(!) detail from The Invention of Drawing, 1830: Karl Friedrich • Roman architect Vitruvius published specifications of plan / elevation drawings, perspective. Illustrations Schinkle (Mitchell p.1) for these writings have been lost Andries van Dam September 15, 2005 3D Viewing I 2/38 Andries van Dam September 15, 2005 3D Viewing I 3/38 1 I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S I N T R O D U C T I O N T O C O M P U T E R G R A P H I C S Most Striking Features of Linear Early Perspective Perspective • Ways of invoking three dimensional space: shading • || lines converge (in 1, 2, or 3 axes) to vanishing point suggests rounded, volumetric forms; converging lines suggest spatial depth -
Squaring the Circle in Panoramas
Squaring the Circle in Panoramas Lihi Zelnik-Manor1 Gabriele Peters2 Pietro Perona1 1. Department of Electrical Engineering 2. Informatik VII (Graphische Systeme) California Institute of Technology Universitat Dortmund Pasadena, CA 91125, USA Dortmund, Germany http://www.vision.caltech.edu/lihi/SquarePanorama.html Abstract and conveying the vivid visual impression of large panora- mas. Such mosaics are superior to panoramic pictures taken Pictures taken by a rotating camera cover the viewing with conventional fish-eye lenses in many respects: they sphere surrounding the center of rotation. Having a set of may span wider fields of view, they have unlimited reso- images registered and blended on the sphere what is left to lution, they make use of cheaper optics and they are not be done, in order to obtain a flat panorama, is projecting restricted to the projection geometry imposed by the lens. the spherical image onto a picture plane. This step is unfor- The geometry of single view point panoramas has long tunately not obvious – the surface of the sphere may not be been well understood [12, 21]. This has been used for mo- flattened onto a page without some form of distortion. The saicing of video sequences (e.g., [13, 20]) as well as for ob- objective of this paper is discussing the difficulties and op- taining super-resolution images (e.g., [6, 23]). By contrast portunities that are connected to the projection from view- when the point of view changes the mosaic is ‘impossible’ ing sphere to image plane. We first explore a number of al- unless the structure of the scene is very special. -
Identifying Robust Plans Through Plan Diagram Reduction
Identifying Robust Plans through Plan Diagram Reduction ∗ Harish D. Pooja N. Darera Jayant R. Haritsa Database Systems Lab, SERC/CSA Indian Institute of Science, Bangalore 560012, INDIA ABSTRACT tary and conceptually different approach, which we consider in this Estimates of predicate selectivities by database query optimizers paper, is to identify robust plans that are relatively less sensitive to often differ significantly from those actually encountered during such selectivity errors. In a nutshell, to “aim for resistance, rather query execution, leading to poor plan choices and inflated response than cure”, by identifying plans that provide comparatively good times. In this paper, we investigate mitigating this problem by performance over large regions of the selectivity space. Such plan replacing selectivity error-sensitive plan choices with alternative choices are especially important for industrial workloads where plans that provide robust performance. Our approach is based on global stability is as much a concern as local optimality [18]. the recent observation that even the complex and dense “plan di- Over the last decade, a variety of strategies have been proposed agrams” associated with industrial-strength optimizers can be ef- to identify robust plans, including the Least Expected Cost [6, 8], ficiently reduced to “anorexic” equivalents featuring only a few Robust Cardinality Estimation [2] and Rio [3, 4] approaches. These plans, without materially impacting query processing quality. techniques provide novel and elegant formulations (summarized in Extensive experimentation with a rich set of TPC-H and TPC- Section 6), but have to contend with the following issues: DS-based query templates in a variety of database environments Firstly, they are intrusive requiring, to varying degrees, modifi- indicate that plan diagram reduction typically retains plans that are cations to the optimizer engine.