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Dorst L., Fontijne D., Mann S. — Geometric algebra for computer science
Dorst L., Fontijne D., Mann S. — Geometric algebra for computer science



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Íàçâàíèå: Geometric algebra for computer science

Àâòîðû: Dorst L., Fontijne D., Mann S.

Àííîòàöèÿ:

Within the last decade, Geometric Algebra (GA) has emerged as a powerful alternative to classical matrix algebra as a comprehensive conceptual language and computational system for computer science. This book will serve as a standard introduction and reference to the subject for students and experts alike. As a textbook, it provides a thorough grounding in the fundamentals of GA, with many illustrations, exercises and applications. Experts will delight in the refreshing perspective GA gives to every topic, large and small. -David Hestenes, Distinguished research Professor, Department of Physics, Arizona State University Geometric Algebra is becoming increasingly important in computer science. This book is a comprehensive introduction to Geometric Algebra with detailed descriptions of important applications. While requiring serious study, it has deep and powerful insights into GA's usage. It has excellent discussions of how to actually implement GA on the computer. -Dr. Alyn Rockwood, CTO, FreeDesign, Inc. Longmont, Colorado Until recently, almost all of the interactions between objects in virtual 3D worlds have been based on calculations performed using linear algebra. Linear algebra relies heavily on coordinates, however, which can make many geometric programming tasks very specific and complex-often a lot of effort is required to bring about even modest performance enhancements. Although linear algebra is an efficient way to specify low-level computations, it is not a suitable high-level language for geometric programming. Geometric Algebra for Computer Science presents a compelling alternative to the limitations of linear algebra. Geometric algebra, or GA, is a compact, time-effective, and performance-enhancing way to represent the geometry of 3D objects in computer programs. In this book you will find an introduction to GA that will give you a strong grasp of its relationship to linear algebra and its significance for your work. You will learn how to use GA to represent objects and perform geometric operations on them. And you will begin mastering proven techniques for making GA an integral part of your applications in a way that simplifies your code without slowing it down. Features Explains GA as a natural extension of linear algebra and conveys its significance for 3D programming of geometry in graphics, vision, and robotics. Systematically explores the concepts and techniques that are key to representing elementary objects and geometric operators using GA. Covers in detail the conformal model, a convenient way to implement 3D geometry using a 5D representation space. Presents effective approaches to making GA an integral part of your programming. Includes numerous drills and programming exercises helpful for both students and practitioners. Companion web site includes links to GAViewer, a program that will allow you to interact with many of the 3D figures in the book, and Gaigen 2, the platform for the instructive programming exercises that conclude each chapter. About the Authors Leo Dorst is Assistant Professor of Computer Science at the University of Amsterdam, where his research focuses on geometrical issues in robotics and computer vision. He earned M.Sc. and Ph.D. degrees from Delft University of Technology and received a NYIPLA Inventor of the Year award in 2005 for his work in robot path planning. Daniel Fontijne holds a Master's degree in artificial Intelligence and is a Ph.D. candidate in Computer Science at the University of Amsterdam. His main professional interests are computer graphics, motion capture, and computer vision. Stephen Mann is Associate Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, where his research focuses on geometric modeling and computer graphics. He has a B.A. in Computer Science and Pure Mathematics from the University of California, Berkeley, and a Ph.D. in Computer Science and Engineering from the University of Washington. * The first book on Geometric Algebra for programmers in computer graphics and entertainment computing * Written by leaders in the field providing essential information on this new technique for 3D graphics * This full colour book includes a website with GAViewer, a program to experiment with GA


ßçûê: en

Ðóáðèêà: Ìàòåìàòèêà/

Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö

ed2k: ed2k stats

Ãîä èçäàíèÿ: 2007

Êîëè÷åñòâî ñòðàíèö: 674

Äîáàâëåíà â êàòàëîã: 04.02.2014

Îïåðàöèè: Ïîëîæèòü íà ïîëêó | Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
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Ïðåäìåòíûé óêàçàòåëü
Subspace products retrieved, proof of grade approach      599—601
Subspaces in linear algebra      10
Subspaces, angle between      68—71
Subspaces, as computation elements      9—12
Subspaces, as operators      188—191
Subspaces, concept      24—25
Subspaces, containment in      76
Subspaces, dual representation      83 190
Subspaces, empty      45
Subspaces, graded algebra of      44—50
Subspaces, Grassmann space of      23
Subspaces, homogeneous      24 42—44 134
Subspaces, intersection/union of      125—140
Subspaces, ladder of      45—46
Subspaces, linear transformations of      99—123
Subspaces, metric products of      65—98
Subspaces, offset      136 280—291
Subspaces, operators on      141
Subspaces, oriented, spanning      23—64
Subspaces, orthogonal projection      83—86
Subspaces, outer product      23—64
Subspaces, projection as sandwiching      190
Subspaces, projection to      155—158
Subspaces, reflections by      188—190
Subspaces, reflections of      168—169
Subspaces, rotations of      169—176
Subspaces, sizing up      66—71
Subspaces, spanning      23—64
Subspaces, squared norm      67—68
Subspaces, transformations as objects      190—191
Subspaces, union of      127
Support points      281 284
Support vectors      281 284 291 316 317
Surrounds      446—447
Surrounds of dual round      446
Surrounds of round      446
Symbolic matrices      525 526
Symmetry, geometric product for vectors      143
Symmetry, subspace products from      152—153
Tangent bundle      406
Tangent(s) of flats      445
Tangent(s) of rounds      445
Tangent(s) without differentiating      445
Tangent(s), 2-blade      404—405
Tangent(s), as intersections of touching rounds      404—409
Tangent(s), circle      223—224 386
Tangent(s), direct      405 461
Tangent(s), dual      406
Tangent(s), flat      445
Tangent(s), plane      86 411
Tangent(s), properties      407
Tangent(s), space      233 236
Tangent(s), vector      405 428 451—454
Tangent(s), vectors, rays as      573—574
Tilting a mirror application      228—230
Transformational changes      215—220
Transformational changes, change of transformation      220
Transformational changes, commutator product      215—217
Transformational changes, rotor-induced      217—219
Transformational changes, transformation of change      219—220
Transformations      see also "Rotation(s)" "Reflection(s)" "Scaling" "Translation(s)" "Versors"
Transformations of change      219—220
Transformations of flats in homogeneous model      335
Transformations of rotors      194
Transformations of standard blades (conformal)      477
Transformations, affine      299 306—308 334
Transformations, as objects      190—191
Transformations, change of      220—221
Transformations, concatenated      191
Transformations, Euclidean      356 364—370
Transformations, loading into OpenGL      348—349
Transformations, nested      191
Transformations, perturbations      217
Transformations, primitives, with OpenGL matrices      349—351
Transformations, projective      299 308—309
Transformations, scene      566—572
Translate-rotate-scale (TRS) versor      471—474 488 489 491
Translation(s) of flats      303
Translation(s) on locations      303—304
Translation(s), algebraic properties      380—381
Translation(s), as versors      380
Translation(s), camera      570—571
Translation(s), covariance      312
Translation(s), dual formula      304
Translation(s), Euclidean k-blade      372
Translation(s), Euclidean transformations      365—366
Translation(s), homogeneous model      303—304
Translation(s), hyperbolic geometry      481
Translation(s), interpolation      266
Translation(s), object      568—569
Translation(s), optimal      262 263
Translation(s), rotations      380—381
Translation(s), spherical geometry      482—483
Translation(s), swapping law      472
Translation(s), translation invariant      380
Transversions      475—477
Transversions, closed-form solution      477
Transversions, defined      475
Triangles, barycentric coordinates      316
Triangles, circumcenter of      457 459
Triangles, line intersection      298 333
Triangles, oriented area      44 251 284 316 427
Triangles, Pascal's      45
Triangles, planar      249—251 284
Triangles, spherical      179—180 252—254
Trifocal constraint      346
Trifocal tensor, as line-parameterized homography      346
Trifocal tensor, defined      345
Trigonometric functions      184—185 531
Trigonometry, planar      249—251
Trigonometry, spherical      251—254
Trivectors, addition of      62
Trivectors, visualization of      36
Two lines in a plane      292—294
Two lines in a plane, coincident lines      294
Two lines in a plane, finite intersection point      293—294
Two lines in a plane, parallel lines      294
Two skew lines in space      295—296
Two skew lines in space, meet      295
Two skew lines in space, relative orientation      298
Underscore constructors in Gaigen2      54—55
Undualization      81
Uniform scaling, as outermorphism example      103
Uniform scaling, point-reflection into origin      109
union      see also "Join"
Union of blades      126 127
Union of subspaces      127
Union, directions      248
Union, encoding      135
Union, magnitude, ambiguity      126
Union, Venn diagram      536
Unit points      274 277
Unit quaternions      181—82
Universal orthogonal transformations      12—14 191—196
Universality      491
Vector differentiation      230—235 see
Vector differentiation of identity function      232
Vector differentiation of inner product      232—233
Vector differentiation of norm      233
Vector differentiation of outer product      233
Vector differentiation, adjoint as derivative      233—234
Vector differentiation, chain rule      234—235
Vector differentiation, framework      230
Vector differentiation, product rule      234—235
Vector differentiation, properties      234—235
Vector fields, example      60
Vector fields, singularities in      60—62
Vector space model      8 247—270
Vector space model, 3-D rotor computations      256—260
Vector space model, angular relationships      248—256
Vector space model, estimation in      260—263
Vector space model, planar reflection      378
Vector spaces      23—25 see
Vector spaces, as modeling tools      8—9 245
Vector spaces, defined      24
Vector Transformations      114—115
Vectors in angular relationships      251 252
Vectors in conformal model      451—455
Vectors in homogeneous model      10 272—278
Vectors in vector space model      10
Vectors with zero norms      145
Vectors, basis      89—90 144—145
Vectors, decomposition      156
vectors, defined      24
Vectors, dividing by      145—146
Vectors, duality      81
Vectors, free      451
Vectors, general, as dual planes and spheres      361—364
Vectors, geometric product for      142—147
Vectors, inverse      79 113—114 145
Vectors, line      453
Vectors, linear transformations of      100—101
Vectors, nonorthonormal      94
Vectors, normal      86 122—123 453
Vectors, null      66 359—361 587
Vectors, orthogonal projection of      84
Vectors, points as      274—278
Vectors, position      451 454
Vectors, ratios, as operators      146—147
Vectors, reflecting in      204
Vectors, squared norm of subspace      67—68
Vectors, support      281 284 291 316 317
Vectors, tangent      453—454
Vectors, unit, ratio      172
Vectors, visualizing      26—27
Velocities      86 88 276
Versor inverse method      530
Versor product      192—193 see
Versor product, blades in      195
Versor product, grade-preserving      194 368
Versor product, orthogonal transformations as      193—195
Versor product, sandwiching      13 190—192
Versor product, structure preservation      368
Versor product, summary      197
Versors      191—196
Versors of composition of operators      193
Versors, computation      220
Versors, conversion to homogeneous $4 \times 4$ matrices      486—493
Versors, defined      195
Versors, Euclidean      364—365
Versors, Euclidean transformations as      364—370
Versors, even      193
Versors, first-order perturbations      386
Versors, inverse      529—530
Versors, logarithm of      532
Versors, odd      193
Versors, orthogonal transformation generation      191—196
Versors, spherical geometry      482—483
Versors, structure-preserving properties      194 364
Versors, test      532—533
Versors, translation      365—366
Versors, TRS      491
Vertices      561—562
Vertices with tangent 2-blades      562
Vertices, storage      561
Visualization, bivectors      31—34
Visualization, conformal model      410—417
Visualization, contraction      75—77
Visualization, outer product      10
Visualization, quaternions      181—182
Visualization, rotations      179—180
Visualization, trivectors      236
Visualization, vectors      26—27
Volumes of simplex      44 427
Volumes, attitude      33
Volumes, elements      33—36
Volumes, orientation      35
Volumes, properties      33—35
Volumes, scalar weight      35
Voronoi diagrams      415—417
Voronoi diagrams, cell analysis      455—460
Voronoi diagrams, defined      415
Voronoi diagrams, determining      416—417
Voronoi diagrams, illustrated      416
Voronoi diagrams, programming example      428—431
Weight, blades      408—409
Weight, defined      43
Weight, directions      248
Weight, lines      26
Weight, points      38 275
Weight, preservation      369
Weight, volumes      35
World points      262—263
X      86
1 2 3 4 5 6
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