Parametric Surfaces Recall That a Curve in Space Is Given by Parametric Equations As a Function of Single Parameter T X = X(T) Y = Y(T) Z = Z(T)
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Unifying Parametric and Implicit Surface Representations for Computer Graphics: Parametric Surface Display and Algebraic Surface Fitting
Purdue University Purdue e-Pubs Department of Computer Science Technical Reports Department of Computer Science 1990 Unifying Parametric and Implicit Surface Representations for Computer Graphics: Parametric Surface Display and Algebraic Surface Fitting Changrajit L. Bajaj Report Number: 90-995 Bajaj, Changrajit L., "Unifying Parametric and Implicit Surface Representations for Computer Graphics: Parametric Surface Display and Algebraic Surface Fitting" (1990). Department of Computer Science Technical Reports. Paper 846. https://docs.lib.purdue.edu/cstech/846 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. UNWYING PARAMETRIC AND IMPLICIT SURFACE REPRESENTATIONS FOR COMPUTER GRAPIDCS: PARAl\ffiTRIC SURFACE DISPLAY AND ALGEnRAIC SURFACEFI1TING Ch:lIldl"lljit L. ll11jllj CSD TR-995 July 1990 Unifying Parametric and Implicit Surface Representations for Computer Graphics: Parametric Surface Display and Algebraic Surface Fitting Chandcrjit Bajaf Department of Computer Science Purdue University West Lafayette, IN 47907 Abstract These are brief survey notes on recent progress in topics dealing with rational surface display aod surface fitting with piecewise algebraic surface patches. It is hoped thai the reader shall delve deeper into specific technical results, by tracking the numerous citations to references provided. Several pictures (unfortnnately grey scale images) are included to illustrate the results of certain algorithms. These notes arc part of a course to be taught at this year's Siggraph 1990. Slides of the course arc also included in the appendix. 'Supported in part by NSF granl D~lS 88-16286 and aNR conlrad NOOOH-88-K-0402 1 1 Introduction Rationality of the algebraic curve or surface is a. -
Surface Integrals
VECTOR CALCULUS 16.7 Surface Integrals In this section, we will learn about: Integration of different types of surfaces. PARAMETRIC SURFACES Suppose a surface S has a vector equation r(u, v) = x(u, v) i + y(u, v) j + z(u, v) k (u, v) D PARAMETRIC SURFACES •We first assume that the parameter domain D is a rectangle and we divide it into subrectangles Rij with dimensions ∆u and ∆v. •Then, the surface S is divided into corresponding patches Sij. •We evaluate f at a point Pij* in each patch, multiply by the area ∆Sij of the patch, and form the Riemann sum mn * f() Pij S ij ij11 SURFACE INTEGRAL Equation 1 Then, we take the limit as the number of patches increases and define the surface integral of f over the surface S as: mn * f( x , y , z ) dS lim f ( Pij ) S ij mn, S ij11 . Analogues to: The definition of a line integral (Definition 2 in Section 16.2);The definition of a double integral (Definition 5 in Section 15.1) . To evaluate the surface integral in Equation 1, we approximate the patch area ∆Sij by the area of an approximating parallelogram in the tangent plane. SURFACE INTEGRALS In our discussion of surface area in Section 16.6, we made the approximation ∆Sij ≈ |ru x rv| ∆u ∆v where: x y z x y z ruv i j k r i j k u u u v v v are the tangent vectors at a corner of Sij. SURFACE INTEGRALS Formula 2 If the components are continuous and ru and rv are nonzero and nonparallel in the interior of D, it can be shown from Definition 1—even when D is not a rectangle—that: fxyzdS(,,) f ((,))|r uv r r | dA uv SD SURFACE INTEGRALS This should be compared with the formula for a line integral: b fxyzds(,,) f (())|'()|rr t tdt Ca Observe also that: 1dS |rr | dA A ( S ) uv SD SURFACE INTEGRALS Example 1 Compute the surface integral x2 dS , where S is the unit sphere S x2 + y2 + z2 = 1. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
16.6 Parametric Surfaces and Their Areas
CHAPTER 16. VECTOR CALCULUS 239 16.6 Parametric Surfaces and Their Areas Comments. On the next page we summarize some ways of looking at graphs in Calc I, Calc II, and Calc III, and pose a question about what comes next. 2 3 2 Definition. Let r : R ! R and let D ⊆ R . A parametric surface S is the set of all points hx; y; zi such that hx; y; zi = r(u; v) for some hu; vi 2 D. In other words, it's the set of points you get using x = some function of u; v y = some function of u; v z = some function of u; v Example 1. (a) Describe the surface z = −x2 − y2 + 2 over the region D : −1 ≤ x ≤ 1; −1 ≤ y ≤ 1 as a parametric surface. Graph it in MATLAB. (b) Describe the surface z = −x2 − y2 + 2 over the region D : x2 + y2 ≤ 1 as a parametric surface. Graph it in MATLAB. Solution: (a) In this case we \cheat": we already have z as a function of x and y, so anything we do to get rid of x and y will work x = u y = v z = −u2 − v2 + 2 −1 ≤ u ≤ 1; −1 ≤ v ≤ 1 [u,v]=meshgrid(linspace(-1,1,35)); x=u; y=v; z=2-u.^2-v.^2; surf(x,y,z) CHAPTER 16. VECTOR CALCULUS 240 How graphs look in different contexts: Pre-Calc, and Calc I graphs: Calc II parametric graphs: y = f(x) x = f(t), y = g(t) • 1 number gets plugged in (usually x) • 1 number gets plugged in (usually t) • 1 number comes out (usually y) • 2 numbers come out (x and y) • Graph is essentially one dimensional (if you zoom in enough it looks like a line, plus you only need • graph is essentially one dimensional (but we one number, x, to specify any location on the don't picture t at all) graph) • We need to picture the graph in two dimensional • We need to picture the graph in a two dimen- world. -
Polynomial Curves and Surfaces
Polynomial Curves and Surfaces Chandrajit Bajaj and Andrew Gillette September 8, 2010 Contents 1 What is an Algebraic Curve or Surface? 2 1.1 Algebraic Curves . .3 1.2 Algebraic Surfaces . .3 2 Singularities and Extreme Points 4 2.1 Singularities and Genus . .4 2.2 Parameterizing with a Pencil of Lines . .6 2.3 Parameterizing with a Pencil of Curves . .7 2.4 Algebraic Space Curves . .8 2.5 Faithful Parameterizations . .9 3 Triangulation and Display 10 4 Polynomial and Power Basis 10 5 Power Series and Puiseux Expansions 11 5.1 Weierstrass Factorization . 11 5.2 Hensel Lifting . 11 6 Derivatives, Tangents, Curvatures 12 6.1 Curvature Computations . 12 6.1.1 Curvature Formulas . 12 6.1.2 Derivation . 13 7 Converting Between Implicit and Parametric Forms 20 7.1 Parameterization of Curves . 21 7.1.1 Parameterizing with lines . 24 7.1.2 Parameterizing with Higher Degree Curves . 26 7.1.3 Parameterization of conic, cubic plane curves . 30 7.2 Parameterization of Algebraic Space Curves . 30 7.3 Automatic Parametrization of Degree 2 Curves and Surfaces . 33 7.3.1 Conics . 34 7.3.2 Rational Fields . 36 7.4 Automatic Parametrization of Degree 3 Curves and Surfaces . 37 7.4.1 Cubics . 38 7.4.2 Cubicoids . 40 7.5 Parameterizations of Real Cubic Surfaces . 42 7.5.1 Real and Rational Points on Cubic Surfaces . 44 7.5.2 Algebraic Reduction . 45 1 7.5.3 Parameterizations without Real Skew Lines . 49 7.5.4 Classification and Straight Lines from Parametric Equations . 52 7.5.5 Parameterization of general algebraic plane curves by A-splines . -
Parametric & Implicit Surfaces
3D Object Representations • Points • Solids o Range image o Voxels o Point cloud o BSP tree Parametric & Implicit o CSG Sweep Surfaces • Surfaces o o Polygonal mesh Thomas Funkhouser o Subdivision • High-level structures Princeton University o Parametric o Scene graph Implicit Application specific COS 426, Spring 2007 o o Surfaces Parametric Surfaces • What makes a good surface representation? • Boundary defined by parametric functions: o Accurate o x = fx(u,v) o Concise o y = fy(u,v) o Intuitive specification o z = fz(u,v) y o Local support o Affine invariant Parametric functions v define mapping from o Arbitrary topology (u,v) to (x,y,z): v o Guaranteed continuity o Natural parameterization x o Efficient display u Efficient intersections u o z H&B Figure 10.46 FvDFH Figure 11.42 Parametric Surfaces Parametric Surfaces • Boundary defined by parametric functions: • Example: surface of revolution o x = fx(u,v) o Take a curve and rotate it about an axis o y = fy(u,v) o z = fz(u,v) • Example: ellipsoid x = r cos φ cos θ = x φ θ y ry cos sin = φ z rz sin H&B Figure 10.10 Demetri Terzopoulos 1 Parametric Surfaces Parametric Surfaces • Example: swept surface • How do we describe arbitrary smooth surfaces o Sweep one curve along path of another curve with parametric functions? Demetri Terzopoulos H&B Figure 10.46 Piecewise Polynomial Parametric Surfaces Parametric Patches • Surface is partitioned into parametric patches: • Each patch is defined by blending control points Same ideas as parametric splines! Same ideas as parametric curves! Watt -
Polygon Meshes and Implicit Surfaces
Polygon Meshes and Implicit Surfaces PPoollyyggoonn MMeesshheess PPaarraammeettrriicc SSuurrffaacceess IImmpplliicciitt SSuurrffaacceess CCoonnssttrruuccttiivvee SSoolliidd GGeeoommeettrryy 10/01/02 Modeling Complex Shapes • We want to build models of very complicated objects • An equation for a sphere is possible, but how about an equation for a telephone, or a face? • Complexity is achieved using simple pieces – polygons, parametric surfaces, or implicit surfaces • Goals – Model anything with arbitrary precision (in principle) – Easy to build and modify – Efficient computations (for rendering, collisions, etc.) – Easy to implement (a minor consideration...) 2 What do we need from shapes in Computer Graphics? • Local control of shape for modeling • Ability to model what we need • Smoothness and continuity • Ability to evaluate derivatives • Ability to do collision detection • Ease of rendering No one technique solves all problems 3 Curve Representations Polygon Meshes Parametric Surfaces Implicit Surfaces 4 Polygon Meshes • Any shape can be modeled out of polygons – if you use enough of them… • Polygons with how many sides? – Can use triangles, quadrilaterals, pentagons, … n- gons – Triangles are most common. – When > 3 sides are used, ambiguity about what to do when polygon nonplanar, or concave, or self- intersecting. • Polygon meshes are built out of – vertices (points) edges – edges (line segments between vertices) faces – faces (polygons bounded by edges) 5 vertices Polygon Models in OpenGL • for faceted shading • for smooth shading -
Surface Normals and Tangent Planes
Surface Normals and Tangent Planes Normal and Tangent Planes to Level Surfaces Because the equation of a plane requires a point and a normal vector to the plane, …nding the equation of a tangent plane to a surface at a given point requires the calculation of a surface normal vector. In this section, we explore the concept of a normal vector to a surface and its use in …nding equations of tangent planes. To begin with, a level surface U (x; y; z) = k is said to be smooth if the gradient U = Ux;Uy;Uz is continuous and non-zero at any point on the surface. Equivalently,r h we ofteni write U = Uxex + Uyey + Uzez r where ex = 1; 0; 0 ; ey = 0; 1; 0 ; and ez = 0; 0; 1 : Supposeh now thati r (t) =h x (ti) ; y (t) ; z (t) hlies oni a smooth surface U (x; y; z) = k: Applying the derivative withh respect to t toi both sides of the equation of the level surface yields dU d = k dt dt Since k is a constant, the chain rule implies that U v = 0 r where v = x0 (t) ; y0 (t) ; z0 (t) . However, v is tangent to the surface because it is tangenth to a curve on thei surface, which implies that U is orthogonal to each tangent vector v at a given point on the surface. r That is, U (p; q; r) at a given point (p; q; r) is normal to the tangent plane to r 1 the surface U(x; y; z) = k at the point (p; q; r). -
An Implicit Surface Polygonizer
An Implicit Surface Polygonizer Jules Bloomenthal The University of Calgary Calgary, Alberta T2N 1N4 Canada An algorithm for the polygonization of implicit surfaces is described and an implementation in C is provided. The discussion reviews implicit surface polygonization, and compares various methods. Introduction Some shapes are more readily defined by implicit, rather than parametric, techniques. For example, consider a sphere centered at C with radius r. It can be described parametrically as {P}, where: β α β α β α ∈ π β ∈ π π (Px, Py, Pz) = (Cx, Cy, Cz)+(r cos cos , r cos sin , r sin ), (0, 2 ), (- /2, /2). The implicit definition for the same sphere is more compact: 2 2 2 2 (Px-Cx) +(Py-Cy) +(Pz-Cz) -r = 0. Because an implicit representation does not produce points by substitution, root-finding must be employed to render its surface. One such method is ray tracing, which can generate excellent images of implicit surfaces. Alternatively, an image of the function (not surface) can be created with volume rendering. Polygonization is a method whereby a polygonal (i.e., parametric) approximation to the implicit surface is created from the implicit surface function. This allows the surface to be rendered with conventional polygon renderers; it also permits non-imaging operations, such as positioning an object on the surface. Polygonization consists of two principal steps. First, space is partitioned into adjacent cells at whose corners the implicit surface function is evaluated; negative values are considered inside the surface, positive values outside. Second, within each cell, the intersections of cell edges with the implicit surface are connected to form one or more polygons. -
Surface Area of a Sphere in This Example We Will Complete the Calculation of the Area of a Surface of Rotation
Surface Area of a Sphere In this example we will complete the calculation of the area of a surface of rotation. If we’re going to go to the effort to complete the integral, the answer should be a nice one; one we can remember. It turns out that calculating the surface area of a sphere gives us just such an answer. We’ll think of our sphere as a surface of revolution formed by revolving a half circle of radius a about the x-axis. We’ll be integrating with respect to x, and we’ll let the bounds on our integral be x1 and x2 with −a ≤ x1 ≤ x2 ≤ a as sketched in Figure 1. x1 x2 Figure 1: Part of the surface of a sphere. Remember that in an earlier example we computed the length of an infinites imal segment of a circular arc of radius 1: r 1 ds = dx 1 − x2 In this example we let the radius equal a so that we can see how the surface area depends on the radius. Hence: p y = a2 − x2 −x y0 = p a2 − x2 r x2 ds = 1 + dx a2 − x2 r a2 − x2 + x2 = dx a2 − x2 r a2 = dx: 2 2 a − x The formula for the surface area indicated in Figure 1 is: Z x2 Area = 2πy ds x1 1 ds y z }| { x r Z 2 z }| { a2 p 2 2 = 2π a − x dx 2 2 x1 a − x Z x2 a p 2 2 = 2π a − x p dx 2 2 x1 a − x Z x2 = 2πa dx x1 = 2πa(x2 − x1): Special Cases When possible, we should test our results by plugging in values to see if our answer is reasonable. -
Villarceau-Section’ to Surfaces of Revolution with a Generating Conic
Journal for Geometry and Graphics Volume 6 (2002), No. 2, 121{132. Extension of the `Villarceau-Section' to Surfaces of Revolution with a Generating Conic Anton Hirsch Fachbereich Bauingenieurwesen, FG Stahlbau, Darstellungstechnik I/II UniversitÄat Gesamthochschule Kassel Kurt-Wolters-Str. 3, D-34109 Kassel, Germany email: [email protected] Abstract. When a surface of revolution with a conic as meridian is intersected with a double tangential plane, then the curve of intersection splits into two con- gruent conics. This decomposition is valid whether the surface of revolution inter- sects the axis of rotation or not. It holds even for imaginary surfaces of revolution. We present these curves of intersection in di®erent cases and we also visualize imaginary curves. The arguments are based on geometrical reasoning. But we also give in special cases an analytical treatment. Keywords: Villarceau-section, ring torus, surface of revolution with a generating conic, double tangential plane MSC 2000: 51N05 1. Introduction Due to Y. Villarceau the following statement it is valid (compare e.g. [1], p. 412, [3], p. 204, or [4]): The curve of intersection between a ring torus ª and any double tangential plane ¿ splits into two congruent circles. We assume that r is the radius of the meridian circles k of ª and that their centers are in the distance d, d > r, from the axis a of rotation. We generalize and replace k by a conic which may also intersect the axis a. Under these conditions it is still true that the intersection with a double tangential plane ¿ is reducible. -
NUMERICAL METHODS for RAY TRACING IMPLICITLY DEFINED SURFACES | Numerical Methods for Ray Tracing Implicitly Defined Surfaces⇤
CS371 2014 NUMERICAL METHODS FOR RAY TRACING IMPLICITLY DEFINED SURFACES | Numerical Methods for Ray Tracing Implicitly Defined Surfaces⇤ Morgan McGuire Williams College September 25, 2014 (Updated October 6, 2014) Figure 1: A 60 fps interactive reference scene defined by implicit surfaces ray traced on GeForce 650M using the techniques described in this document. Figure 2: An impressive demo of real-time ray-traced implicit surface fractals by Kali (Pablo Roman Andrioli), implemented in about 300 lines of GLSL https://www.shadertoy.com/ view/ldjXzW. ⇤This document is an early draft of an upcoming Graphics Codex chapter. http://graphics.cs.williams.edu/courses/cs371 1 Contents 1 Primary Surfaces 3 2 Analytic Ray Intersection 3 3 Numerical Ray Intersection 3 4 Ray Marching 4 5 Distance Estimators 5 6 Sphere Tracing 5 7 Some Distance Estimators 6 7.1 Sphere ......................................... 6 7.2 Plane ......................................... 6 7.3 Box .......................................... 6 7.4 Rounded Box ..................................... 7 7.5 Torus ......................................... 7 7.6 Wheel ......................................... 7 7.7 Cylinder ........................................ 8 8 Computing Normals 8 9 A Simple GLSL Ray Caster 9 10 Operations on Distance Estimators 11 11 Some Useful Operators 12 11.1 Union ......................................... 12 11.2 Intersection ...................................... 12 11.3 Subtraction ...................................... 12 11.4 Repetition ......................................