Ãëàâíàÿ    Ex Libris    Êíèãè    Æóðíàëû    Ñòàòüè    Ñåðèè    Êàòàëîã    Wanted    Çàãðóçêà    ÕóäËèò    Ñïðàâêà    Ïîèñê ïî èíäåêñàì    Ïîèñê    Ôîðóì   
blank
Àâòîðèçàöèÿ

       
blank
Ïîèñê ïî óêàçàòåëÿì

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



Îáñóäèòå êíèãó íà íàó÷íîì ôîðóìå



Íàøëè îïå÷àòêó?
Âûäåëèòå åå ìûøêîé è íàæìèòå Ctrl+Enter


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
blank
Ïðåäìåòíûé óêàçàòåëü
Grassmann algebra, defined      48
Grassmann space      23 48
Grassmann, H.      10 24
Hesse normal form      290
Hestenes product      518 590
Hestenes, D.      388
Hodge dual      135
Homogeneous coordinates      8 245 271 302 338
Homogeneous coordinates as imaging      339—340
Homogeneous coordinates, geometric algebra and      245
Homogeneous lines      25—26
Homogeneous model      8—9 245 271—326
Homogeneous model as imaging      339—340
Homogeneous model, affine transformations      306—308
Homogeneous model, applications      327—354
Homogeneous model, coordinate-free parameterized constructions      309—312
Homogeneous model, direct/dual representation of flats      286—291
Homogeneous model, element construction      305—306
Homogeneous model, embedded in conformal model      374
Homogeneous model, equations      606
Homogeneous model, general rotation      305
Homogeneous model, geometric algebra specification      273
Homogeneous model, incidence relationships      292—301
Homogeneous model, k-flats as (k + 1)-blades      285—286
Homogeneous model, linear transformations      302—309
Homogeneous model, lines as 2-blades      278—283
Homogeneous model, matrices vs conformal versors      486—492
Homogeneous model, metric of      272—273
Homogeneous model, metric products      312—315
Homogeneous model, modeling principle      271
Homogeneous model, non-Euclidean results      312—313
Homogeneous model, nonmetrical orthogonal projection      314—315
Homogeneous model, planes as 3-blades      283—285
Homogeneous model, points as vectors      274—278
Homogeneous model, projective transformations      308—309
Homogeneous model, representation space      272—73
Homogeneous model, rigid body motion      305 334—335
Homogeneous model, rigid body motion outermorphisms      306 334—335
Homogeneous model, rotation around origin      304
Homogeneous model, translations      303—304
Homogeneous planes, attitude      27—28
Homogeneous planes, measure of area      28
Homogeneous planes, orientation      28
Homogeneous Pluecker coordinates      328—336
Homogeneous Pluecker coordinates, 4-D representation space      336
Homogeneous Pluecker coordinates, combining elements      332—333
Homogeneous Pluecker coordinates, defined      328
Homogeneous Pluecker coordinates, elements in coordinate form      330—332
Homogeneous Pluecker coordinates, line representation      328—330
Homogeneous Pluecker coordinates, matrices of motions      334—335
Homogeneous subspaces      23 see
Homogeneous subspaces of 3-D space      25
Homogeneous subspaces, defined      24
Homogeneous subspaces, direct representation      43
Homogeneous subspaces, representation      42—44
Hyperbolic functions      184—185
Hyperbolic geometry      480—481
Hyperbolic geometry, defined      480
Hyperbolic geometry, illustrated      481
Hyperbolic geometry, motions      481
Hyperbolic geometry, translations      481
Hyperplanes in Pluecker coordinates form      331
Hyperplanes, dual representation      290
Hyperplanes, normal equation      290
Identity function      225 232
Image geometry      499
Imaginary rounds and flats      400
Imaging by multiple cameras      336—346
Imaging by multiple cameras, homogeneous coordinates      339—340
Imaging by multiple cameras, line-based stereo vision      342—346
Imaging by multiple cameras, pinhole camera      337—339
Imaging by multiple cameras, stereo vision      340—342
implementation      503—581
Implementation of general multivector class      547—549
Implementation of specialized multivector class      549
Implementation, algebra specification      546—547
Implementation, alternative approaches      505—508
Implementation, crystallography      267—268
Implementation, efficiency issues      541—543
Implementation, function optimization      550—552
Implementation, geometric algebra      503—509
Implementation, goals      544—545
Implementation, issue resolution      544—546
Implementation, levels      504—505
Implementation, linear products      521
Implementation, nonlinear function optimization      553—554
Implementation, outermorphisms      552—553
Implementation, software      16—17
incidence      see also "meet"
Incidence, "co-incidence"      439
Incidence, computation examples      292—296
Incidence, Euclidean      438—444
Incidence, relationships      292—301
Incidence, relative lengths      298—301
Incidence, relative orientation      296—298
Incidence, two lines in a plane      292—294
Incidence, two skew lines in space      295—296
Infinite k-flats      285
Infinite points      275—276
Inner products      see also "Products"
Inner products of spheres      417—418
Inner products, conformal model      361
Inner products, defined      66 589—596
Inner products, Differentiation with a vector-valued linear function      225
Inner products, distance of spheres      417—418
Inner products, dot      518 589—590
Inner products, generalization      4 67
Inner products, Hestenes'      590
Inner products, near equivalence of      590—591
Inner products, scalar differentiation      225
Inner products, vector differentiation      232—233
Interpolation      491
Interpolation, rigid body motion example      395—396 493—494
Interpolation, rigid body motions      385—386
Interpolation, rotation      259—260 265—267
Interpolation, slerp      260
Interpolation, translations      266
intersections      7 see
Intersections of blades      127
Intersections of Euclidean circles      414
Intersections of lines      333
Intersections of spheres      405
Intersections, conformal primitives and      432—434
Intersections, directions      248
Intersections, encoding      135
Intersections, finite points      293—294
Intersections, magnitude, ambiguity      128
Intersections, offset lines      293
Intersections, phenomenology      125—127
Intersections, planar lines      41
Intersections, plane      86—87 88 130
Intersections, primitives      322—324
Intersections, ray-model      577—579
Intersections, tangents as      404—409
Intersections, through outer factorization      127—128
Intersections, Venn diagram      536
Invariance of properties      369—370
Inverse kinematics      423—426
Inverses      491
Inverses, blades      128—129 155 529—530 554
Inverses, multivectors      155 530—531 554
Inverses, orthogonal matrix      110
Inverses, outermorphisms      113—114
Inverses, pseudoscalar      113
Inverses, rotors      183
Inverses, vectors      79 113—114 145
Inverses, versors      128—129 529—530
Inversion of various elements      467
Inversion, defined      465
Invertible geometric product      142—143
Involution of basis blades      519
Involution, grade      50 604
Irreducible matrix implementations      507—508
Isometries      356
Isomorphic matrix algebras      506—507
Jacobi identity      216
Join of blades      536—540 554
Join, as mostly linear      131—132
Join, benchmark      139
Join, computation algorithm      537—540
Join, efficiency      139
Join, floating point issues      139—140
Join, meet relationship      128—129
Join, preservation      135
Join, programming example      138—139
Join, using      129—130
Join, Venn diagram      537
Julia fractals      208—210
Julia fractals, 2-D      211
Julia fractals, 3-D      212
Julia fractals, code      210
Julia fractals, defined      208
k-blades      68
k-blades, angle between subspaces      69—70
k-blades, as outer product of vectors      46
k-blades, defined      44
k-blades, grade      44
k-blades, k-vectors versus      46—47
k-blades, number of      45
k-flats      285—286
k-flats, infinite      285
k-flats, parameters      285—286
k-vectors, k-blades versus      46—47
k-vectors, simple      46
k-vectors, step      46
Kinematics      420—426
Kinematics, forward      420—422
Kinematics, inverse      423—426
Kronecker delta function      515
Left contraction      77 518 590
Lie algebra      219
Line vector      453
Line-based stereo vision      342—346
Linear algebra      8
Linear algebra on composite elements      17
Linear algebra, constructions      14—15
Linear algebra, implementation approach      522—526
Linear algebra, planar reflection      377—378
Linear algebra, subspaces in      10
Linear equations with bivectors      40
Linear equations, solving      39—40
Linear operations      522—523
Linear products      521—527
Linear products, implementation      521
Linear products, linear algebra approach      522—526
Linear products, list of basis blades approach      526—527
Linear products, types of      521
Linear transformations      99—123
Linear transformations of blades      101—108
Linear transformations of contraction      109—10
Linear transformations of cross product      112
Linear transformations of metric products      108—112
Linear transformations of scalar product      108
Linear transformations of subspaces      99—123
Linear transformations, adjoint of      108—109
Linear transformations, as outermorphisms      101
Linear transformations, defining properties      100
Linear transformations, determinant of      106—107
Linear transformations, efficiency      201 552—553
Linear transformations, equations      605
Linear transformations, extended      7 12
Linear transformations, homogeneous model      302—309
Linear transformations, implementation      532—553
Linear transformations, inverse of      113—114 119
Linear transformations, join      133—136
Linear transformations, matrix representation      114—117
Linear transformations, meet      133—136
Linear transformations, orthogonal transformations      110—111
Linear transformations, point at origin under      103
Linearity, geometric product for vectors      144
Linearity, geometric product of multivectors      148
Lines at infinity      282
Lines in coordinate form      331—332
Lines, addition of      282—283 324—325
Lines, as 2-blades      278—283
Lines, attitude      26
Lines, circular orbits      444
Lines, closest points computation      353—354
Lines, coincident      294
Lines, distance measure along      26
Lines, edge      455—456
Lines, finite      278—282
Lines, homogeneous      25—26
Lines, intersecting      333
Lines, moment      279
Lines, oriented      26
Lines, parallel      294
Lines, planar, intersecting      41
Lines, Pluecker coordinates      328—336
Lines, plunge      443
Lines, projection onto      103—104
Lines, reflection      4 167 168
Lines, representing with point pairs      579
Lines, skew      295—296 333
Lines, specification      279
Lines, two, in a plane      292—294
Lines, weight      26
List of basis blades approach      526—527
Locations, blades      409
Locations, translations on      303—304
Locations, weighted points at      313
Logarithms      187—188
Logarithms of 3-D rotor      258—269
Logarithms of rigid body motion      383—385 493
Logarithms of scaled rigid body motion      473—475 493—495
Logarithms of translation      389
Logarithms of versors implementation      532
Loxodromes      478—479
Marker reconstruction      351—354
Marker reconstruction in optical motion capture      351—354
Marker reconstruction, algorithm      352—353
Marker reconstruction, defined      351
Marker reconstruction, illustrated      352
Matrices for linear transformation of vectors      200
Matrices for outermorphisms      115—117
Matrices for vector transformations      114—115
Matrices of motions in Plucker coordinates      334—335
Matrices, defined      114
Matrices, essential      342
Matrices, metric      419 515
Matrices, OpenGL      349—351
Matrices, rigid body motion outermorphisms as      306
Matrices, symbolic      525
Matrix multiplication      523
Matrix representations      114—117
Matrix representations of linear transformation      114
Matrix representations, example      120—122
Matrix representations, outermorphisms      122
Matrix-rotor conversion      204—208
Matrix-to-versor conversion function      488
Meet in conformal model      438—440
Meet in homogeneous model      292—298
Meet, argument order      134
Meet, as mostly linear      131—132
Meet, computation algorithm      536—540
Meet, conformal model      438
Meet, defined      127—129
Meet, efficiency      139 536—540 554
Meet, factorization of      138
Meet, join relationship      128—129
1 2 3 4 5 6
blank
Ðåêëàìà
blank
blank
HR
@Mail.ru
       © Ýëåêòðîííàÿ áèáëèîòåêà ïîïå÷èòåëüñêîãî ñîâåòà ìåõìàòà ÌÃÓ, 2004-2024
Ýëåêòðîííàÿ áèáëèîòåêà ìåõìàòà ÌÃÓ | Valid HTML 4.01! | Valid CSS! Î ïðîåêòå