VTK 3.0：面向对象的3D图形教程（附社区资源）

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《The Visualization Toolkit (VTK)：面向对象的3D图形方法》是一本经典的入门与开发书籍，第三版由Will Schroeder、Ken Martin和Bill Lorensen共同编著，特别贡献者包括Lisa Sobierajski Avila、Rick Avila和C.Charles Law。这本书旨在向读者介绍VTK——一个强大的3D图形可视化工具包，它采用面向对象的设计方法，广泛应用于科学可视化、医学成像、工程模拟等领域。本书详细介绍了VTK的核心概念，如几何体建模、数据结构、渲染管线以及交互技术等，使读者能够掌握如何构建和定制自己的3D图形应用程序。通过阅读，开发者将了解到如何利用VTK处理和显示各种类型的数据，包括点云、网格数据和流线等，并实现复杂场景的渲染和动画效果。此外，书中还提到了VTK社区的重要角色，鼓励读者参与社区交流，分享经验和技术，以促进技术的发展。Kitware公司，作为VTK的主要支持者，提供了商业咨询服务，并强调了软件的版权信息，指出未经许可，不得复制或以任何形式传播这本书的内容。如果你需要进一步的信息或者购买套印版以获取更丰富的配套资源，可以访问Kitware官网（http://www.kitware.com），或者通过电子邮件联系官方（rokirware@kitware.com）。 Kitware在可视化技术领域处于领导地位，他们的产品和服务反映了对高质量和创新的承诺。总结来说，《The Visualization Toolkit》是一本深入浅出的指南，不仅适合初学者入门，也对有经验的开发者提供实用的参考，帮助他们提升3D图形处理和可视化能力。通过学习这本书，读者将能够充分利用VTK的强大功能，推动科学研究和工业应用中的可视化工作。

AcknowIedgm6flts

visualization sySlemll m lhe world today. sebastien Barre. Andy Cedilnik. Berk

eci. Amy

Hender<.on. and Brad King have each made signiricanl contributIons. Thank also

the rolks

GE Global Research such as Jim Miller who continue to

pmh

the quali£y

the

~ystem.

particularly with the creation of the DART system ror regression

te~ting.

The

National

Labs. led

Jim

Ahren~

Los Alamos. has been

ill~lrulllcllllll

ill

adding parallel

proce~sing

<'upport

to VTK. An additional special thanks

Kilware ror accepting the challenge

pub-

Ii~hing

Ihis book.

Many

Ihe bug

fix~

and

improvemcn~

round

the second

and

third edItions came

rrom

lalented people located around the world. Some

these people are acknowledged

the soflware and

ehewhcre

in the

ICl(t.

but most

olthcm

have contnlJuted their tIme. kIlo""l-

edge. code. and dala ""lthOul regard for recognition and acknowledgment.

is Ihis exchange

ideas and information with people like this that makes Ihe

ViSUldi:.lltion

Toolkit such a

fun

and exciting project

work on.

partjcular we would like to thank John Blddiscombe.

Charl

Sotha. David Gobbi. Tim Hulton. Dean Inglis. and Prabhu Ramachandmn. Thank

you very much.

A special thanks

the soflware and text reviewers who Spclll their own time

track

down some nasty bugs. provide examples. and offer

suggeslion!'>

and impro

....

ements. Thank

you Tom Citrinill. Mark Miller. George Petras.

Han'>Ong

Zhang. Penny Rhemgans. Paul

Hinker. Richard Elison. and Roger Crawfis. We'd

also like

mention thai Tom Citriniti

Rensselaer. and Penny Rheingans at the Uni\'eThlly

MissiSSippi (now at the Uni\'er.;ity

Maryland Baltimore County) were the firsl faculty members

leach from early '

mioll!>

Ihi

text. Thank you Penny and Tom ror your

reedbad

and eXira effort.

Most importantly we would like to thank our friends and loved one

who supported us

patIently during

thi~

project.

know that you shouldered extra load

for

us.

You

certainly

saw

3 lot less

us! But we're happy to

SllY

thaI we're back. Thank you.

•

2 IntlOduclion

neering. Such daw sources include financial, marketing.

business data.

addition. the

term

data visuali73tion

broad enough to include application ofstatistical methods

and

other

standard data analysis

tcChJliques

[Rosenblum94]. Another recently emerging tcnn

illfor.

mation

vimaliZiltioll.

This field

cndeavor~

to visualize abstract informatiOn

such

hyper·

text t10cumellb on the World Wide Web,

directory/file

structures on a

compuLCr.

abstract

daln structures {lnfoVis951. A majorchal1eoge facing infonnation visualization

re~archers

develop

coordinale ily<;lcms. lrnn<,(onnalion methods.

StruCIUf'el>

Ihal

meamngfully

orga-

nize and

repre~nl

claw

Another

way

classify

"i!>ualizalion

tcchnology

examine the context

which

the:

data

e:tists. If the

data

spatial·tempoml

in nature

(up

to three

~patial

coordinates

and

the

time

dimension)

then typically

methods

from scientific

visualllation

are used.

the

d.:lta

ex.i~h

in higher-dimensional spaces.

abstract spaces. then methods from

infonnation

visu-

alization are used.

This

distinction is

imponaru.

because

the human perceptual system is

highly tuned

space-time

relationships. Data

expressed

in this

coordinate

system is inher-

ently

understood with litlle need for explanation. Visualilation

abstract

dat.1

typically

requires

extensive

explan:ILiults

wl1m

is being viewed. Thi

not

say thut there is no

overlap

between

!oCicntific

and

IOfonnation vi

ualization-often

the

first

step

in the infonna-

tion visualIzation process is

project abstract

data

into

the spatial-temporal domalO. and

then

the

methoch

..cientific visualization to view

the

~ults.

The projection process

can

quite

complex., Involving methods

statistical

graphics.

dam mining.

and

other

toch-

nique.s.

it may

a:.

simple

selecting a 10\Ver-dllnensional sub:.et

the

ongmal

dma.

In this text

usc

the

teml

dala

visualization tnstead

the

specific

tenns

ien-

tific visualization

information visualization.

feel that scientific visualization is too nar-

row (l description

the field,

<,ince

visuali

ation techniques hilve

moved

beyond the

scientific

domain

and inlo areas

business. social science. demographics, and lIlformation

management

in gener..tl.

al'\() feel that the term

data

visualization is brood enough to

encompas~

the

tenn

mformation vi<,ualization.

Examples

Visualization

Perhaps tile

best

defimtion

vi!>uali7ation is offered by

example.

many

cases

Visualization

innuencing

peoples' lives

and

perfomling

feats that a few

ye:m

ago would have been

unimaginable. A

primc

examplc

this

its application

modern medicine.

Computer

imaging techniques have

become

imponam

diugnostic tool

the praclice

modem

medicine.

These

include techniques

such

X-ray

Computi!d Tomograp/l)'

(Cf)

and

Mag"etic

Re~o"allce

Imaging (MRl).

The.<.e

lechniques U\e a

sampling

data

acquisi-

tion

p"oce~s

capture

infonTIation

about

the

internal

anatomy

a living pallelll, This infor-

malion is in the

(onn

sUa-planes

crosS·\eCtlonal

lmage..'i

a patient. similar

comemional

photogrnphlc X-rays.

imaging

u~s

many

pencil thin

X-rays

acquire the

data. whiJe MRI

combmes

large

magnetic

fields with pulsed radio wa,·es. Sophisticated

mathematical techniques are used to

reconstruct

the

slice-planes. Typically.

many

such

closely

spaced

slices are gathered together into.1

mlume

data

complete

the

~Iudy.

As acquired from Ihe imaging syMelll, a

slice

serie~

numbers representing the

attenuation

X-ray!>

(CT)

the relaxation

nuclear

spin magnctizJtjon (M RI) IKrestel90].

any

given

~lice

these

numbers

are

arranged in a matrix.

regular

army.

The

amount

data

large.

large

that it is not

pos\ible

undel"!ttand

the

data

in its

raw

fonn.

However,

1 2 Why Visualize?

assigning

these

numbers

gray

scale

value.

and

then dll>playmg

the

data

on a

computer

screen.

structure

emerges.

This

Mructure results from

the

interaction

the

human

\'i'oual sys-

tem with

the

spatial organization

the

data

and

the

gray-scale

values

hu\c

chosen.

What

the

computer

rcpresents as a series

numbers.

see

cross

section through the human

body:

skin. bone.

and

muscle.

Even

more impressive results arc possible when

extend

the~

techniques

into

three

dimensions.

Image

slices

can

g~t(hered

into

volumes and the

volumes

can

processed

....

eal

complete

anatomical

tructu~.

Using

modem

tech-

mques.

can

view

the

entire

brain.

skeletal

system,

and

vascular

system

a lIVIng patient

wilhout inteT'\'entional surgery.

Such

capability

ha.-',

re\'olutioniled

modem

medical diagnos-

tics.

and

will increa!>e in

importance

as imaging

and

....

isualization lechnology

malU~.

AnolJler e

....

eryday

application

"isuaIi7a!lon i

in lhe

entertainmenl

mdustry.

MO\ie

and television

producers

routinely use

compuler

grnphics and Visualization

create

entire

worlds that

could

never

vblt

our

physical bodies.

thcsc

c:tscs

nrc visuali/.ing

other

world:; as

imagine

them,

pa,t

worlds.

suppose existed. [t's hard to watch lhe

movies

such

)lIm,Hie

Park and Toy

Swry

and not gain a

deeper

appreciation for the :'lwe-

some

Tyrannosaurus

Rex,

cham-ed

by Tor Story's heroic

Buzz

Lightyear.

Morphing

another

popular

\Isuahzation

technique

....

idely

used

the

entertainment

IIldustTy.

Morphmg

is a

smooth

blending

one

object

into

another.

One

common

application

morph

betwocn

two

faces.

Morphing

has

also

been lbed

effectively

lllumate

car

de\lgn

changes

from

one

year

to the next.

While

thi

may

<;eCm

like an c<;oleric application.

\ISUah7.a1ioll

techmques

are

u'>Cd

routinely to pre<,tnl the daily

weather

report.

The

use

i-'iOvalue,

contour, lines

display

areal>

con~tanl

temperature. rainfall, and barometric

pressure

has

become

a standard tool in the daily

wcmher

report.

Many

early

uses

vi~ualization

were

the

engineering

and scientific community.

From its inception the

computer

has been used

a tool to

simulate

physical processes such

as ballistic trajectories, fluid flow,

and

structuralmcehaIlics.

As the size

the

computer

sim-

ulations

gre

.....

became

necessary

10 lnlnsform lhe resultlllg

calculations

1Il1O

pictures.

The

amount

data

o\erwhdmed

the

ability

the

human

asSimilate

and

understand

II.

In fact.

pictures

were

important that early \ isualizations

were

created

by manually plott

109

data

Today.

can

take

advantage

....

ances in

computer

graphics

and

computer

hard\\.

ate.

But.

whate

the

lechnology, the

application

visualizallon is the

same:

to display the

~UIL\

simulatIons.

experiments,

measured

dala.

and

fantasy:

and

to use

these

pictures

communi-

cate,

understand,

and entertain.

1.2

Why

Visualize?

Visualization is a neceli..ary tool to

make

sen-.e

the flood

infonnalion

III

today's

....

orld

computers. Satellites.

supercomputers.

laser digitiLing

systems.

and

digital

data

acqUisition

systems

acquire. genernte.

and

transmit data at

prodigious

rates.

1bc

Earth-Orbiting Satellite

(EOS)

transmits terabytes

data

e\ery

tla).

La!'>Cr

scanning

sy"lcms

generate

o\er

500.000

points

III

second

scan

[Waters9IJ.

Supercomputers

model

weather

patterns

over

the

entire

earth [Chen931. In the first four months

1995.

the

New

York Stock

Exchange

pro-

cessed,

average,

333 million transactions

per

day

[NYTimcsl.

Wilhout visualillition. most

this

data

would

sit

unseen on

computer

disks

and

tapes. Visualizlltioll

offer;

~ollle

hope

that

can

extmct

the important information hidden within the data.

IntroductlOll

There

another

Important

element to visualization:

tales

advantage

the natural

abilities of the human

ion system.

Our

vision system

a complex and powerful

p:lrt

our

bodies.

u<;c

and

rely

almo!.! everythmg we do. Given Ihe environment

which

our

ancestors li\'ed.

is not surprising

t.hal

certain seru.es de\'eJoped

help

them

5UI"\'l\-e.

described earlier

the example

l.I

MRI

scan. vi,unl rel,resentallon'!,

are

easier

work wilh. Not only do we have strong 2D visual abilities. but also

arc adept

integrat-

ing dirferent vie"'points and other visual clues into a meow' image

object

plot.

This leads

interacthe

\'isualization.

"here

we can mampulate our slev.'point. Rotating

about the object helps

achic\ie a better undeNtanding. Likew Ise. we

ha\c

a talent for recog·

nizing tcmporal ch:lngcs in

imagc. Given an :lnirmltlon

consi~ting

hundreds

fnunes,

we ha\'e

uncanny ability

recOglll1.e

trends and spot

area\

rapid change.

With the illlroduclion

computers and the ability

~enerate

enormous amounb.

data. visuali/ation

offcr<;

the technology to make the best use

our

highly developed visual

ense~.

Certainly other technologies

~uch

il~

stati'itical analy

is. artificial IIltclligcnce, mathe·

matical filtering. and sampling theory will

playa

role

III

large-scalc dala processing. How-

er. because \"isualizalion directly

en~age\

the vision system and human brain.

fCnl81llS

unequaled technology for

undcr~tandlng

and commulllcating data.

Visualilation offers sigllllicant financial advantages as well.

loday'.., competitive

markets. computcr

~Imulation

teamed

....

ilh

isuali7.3lion

can

reduce product

CO\t

and Improve

lime

market. A large

c~t

product

de<;ign

has been the

expen<,e

and time required to cre-

ate

and test design prototypes. Current de

...

ign method

stri\'e to ehmin:Hc the'ie

phy<;ical

pro-

totypes. and

replace them with digital equivalcnts. This digital prololyping requires the

abilily to create

and manipulate product geomctry. simulate the design under a \ariely

operatlllg conditions. develop manufacturing techniques. demon<;trate product maintenance

and

service

procec..lures.

and even train operators on Ihe proper use

Ihe product before

buill.

Vi"u31i1·.3tion

plays a role

c:lch case. Already

CAD

system" are used routinely

model product geometry and design manufacturing procedures. Visualilation enables

vic,",

lhe goomeu),. and <,ee special characlerist.ic!> such a

...

surface cun-aluft. For inslance.

analysis techniques

such as finite element. finite difference. and boundary element tech-

niques are

used to simulate product pcrfomlunce: and \'i<;ualization

used to view the

results. Recently. human ergonomics and anthropometry are being analyzed

u<,mg

computer

techniques

combination wilh visualizalion IMDHMSl Three.cJ.imensional

~raphics

and

visuahlation

are being used

create traming sequences. Often these are Incorporated illlo a

hypcrtext documenl or World Wide Wcb (WWW) pages. Another practical

graphics

and

vi<,uaJi/ation has been in-night simulators. This has becn shown

a significant cost-

s.wings as compared

flying real airplanes

and

an cffe<.:ti\c training method.

1.3

Imaging,

Computer

Graphics,

and

Visualization

Therc

confusion surrounding Ihe difference belween imaging.

cOl1lpUler

graphics. and

visu<llization.

offer these definitions.

•

hnagmg.

image processing.

Ihe study

2D PlcIUfe\. or

Image~_

Thi~

IIlclude5

techniques

to tmnsform (e.g

I"()(ale.

scale. shear). extract IIlforrnalion from. analyze.

and enhance

images.

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