1、關(guān)于套話表述：
for starters 第一點(diǎn)，用于代替常用的firstly, first of all等等
more importantly 更重要的是， 用于代替second, for another thing...等等
the icing on the cake 更棒的是，超級(jí)加分用法！一定要掌握的說(shuō)法
E.g. describe a job you would like to pursue in the future. Use specific details and examples to illustrate why you want to get this job.
Speaking of my future job, I would like to be a marketing director in a global top company.
For starters, it is definitely a chanllenging job which can make me feel fulfilled! This job will make me completely understand the ture meaning of " a sense of satisfaction and achievement." The icing on the cake is that the high annual salary, the tempting bonus and satisfying welfare benefits will meet my material demands! And I can also build up a network of professinal contacts when I work with PR agency and institutes, which is quite important in this whole industry!
On the top of it, this field has great career prospects! These are what I love about my job and give me strong incentive to work even harder. And I believe this job helps me to realize my full potential!
注意我用紅色筆標(biāo)注的加分內(nèi)容，這些都是非常地道的口語(yǔ)說(shuō)法，在下面我會(huì)羅列
for starters 第一點(diǎn)
sense of satisfaction and achievement 成就感和滿足感
The icing on the cake 更棒的是
high annual salary, the tempting bonus and satisfying welfare benefits 高收入，豐厚的年終獎(jiǎng)和誘人的福利待遇
has great career prospects 很棒的職業(yè)前景
give sb strong incentive to .強(qiáng)烈的驅(qū)使某人做某事
realize one's full potential 實(shí)現(xiàn)某人全部潛能
今天的加分用法記下來(lái)了么？哈哈，希望大家在遇上職業(yè)描述類(lèi)的時(shí)候可以用上，這些加分詞匯同樣可以用在major等描述里面
轉(zhuǎn)自:http://blog.sina.com.cn/s/blog_5d874c650100h8nm.html
正能量(Rip it up,the radically new
approach to changing your life)
參考亞馬遜書(shū)評(píng).
//大致介紹
the Richard Wiseman'new book-rip it up,the radically new approach to changing your life-bring a whole heap of revolutionary psychology studies that turn your idea about how to change upside down.
//主題思想
it express a key idea that something so simple can be effective in changing someone's life.
//主題思想展開(kāi)
The idea is that we have confused the horse with the cart(習(xí)語(yǔ),混淆因果關(guān)系)-
compared with the theory which tells us how to change the way we think, it's far easier to change the way we act in simple & subtle ways.
//具體例證
Want to feel happier? Force yourself to smile & you will actually feel better.
Want to be more confident? Stand in a confident pose & it will effect how you see yourself.
馬斯洛需求金字塔(Maslow's hierarchy of
needs.)
參考wiki.
physio logical needs:food,water
safety:health,body
love:friendship,family
esteem:confidence,respect of others.
self-actualization:creativity,morality
喬布斯(Steven Jobs) 7加t,工作s.
參考喬布斯在斯坦福大學(xué)演講。
//關(guān)鍵詞:謙虛，進(jìn)取
Key:as the proverb goes ,stay hungry , stay foolish
dropped out of college after the first 6 months.
following my curiosity and intuition turned to be priceless in the future.
//關(guān)鍵詞:機(jī)遇，興趣
first:calligraphy class
if Jobs never dropped in on that single course in college, the Mac would never have multiple typefaces.
//關(guān)鍵詞:挫折
//陳述背景
second story:love and loss
Jobs started Apple in his parent's garage when he was 20.They worked hard and in 10 years Apple had grown from just the two people in a garage into a 2 billion company with over 4000 employees.And he had just turned 30 and then he got fired.
(Jobs got fired by the company he started)
//轉(zhuǎn)折原因
he had been rejected but he was still in love.
it is dream and love that drive him to start over.
one of the most creative period of his life.He started another company named NeXT.
//哲學(xué)總結(jié)
It was awful tasting medicine but the patient needed it.
don't lose faith. Do what you love.Don't settle.
persistence.
//例子沒(méi)用，記住幾個(gè)句型
//關(guān)鍵詞:走自己的路
third story:death
If you live each day as if it was your last,someday you'll most certainly be right.
every thing - all external expectations, all pride, all fear of embarrassment or failure will fall away in the face of death.You are already naked so that there is no resson not to follow your heart.
Don't be trapped by dogma, don't let the noist of others' opinions drown out your own inner voice.
Have the courage to follow your heart and intuition.
情商
EQ(emotional quotient)
//參考google.
//EQ作用
EQ is sometimes described as more important than IQ since EQ helps us to understand our life, our values better.
//證據(jù)
plenty of experiments indicate that having better EQ is a must for making healthy choices in every aspects of life.
//再展開(kāi)，一般用不到。
functions:
1.know and manage your own emotions.
2.motivate ourselves.
3.influence others'emotions.
4.handle relationship.
以下鏈接是本人整理的關(guān)于計(jì)算機(jī)視覺(jué)（ComputerVision, CV）相關(guān)領(lǐng)域的網(wǎng)站鏈接，其中有CV牛人的主頁(yè)，CV研究小組的主頁(yè)，CV領(lǐng)域的paper,代碼，CV領(lǐng)域的最新動(dòng)態(tài)，國(guó)內(nèi)的應(yīng)用情況等等。打算從事這個(gè)行業(yè)或者剛?cè)腴T(mén)的朋友可以多關(guān)注這些網(wǎng)站，多了解一些CV的具體應(yīng)用。搞研究的朋友也可以從中了解到很多牛人的研究動(dòng)態(tài)、招生情況等。總之，我認(rèn)為，知識(shí)只有分享才能產(chǎn)生更大的價(jià)值，真誠(chéng)希望下面的鏈接能對(duì)朋友們有所幫助。
(1)googleResearch； http://research.google.com/index.html
(2)MIT博士，湯曉歐學(xué)生林達(dá)華； http://people.csail.mit.edu/dhlin/index.html
(3)MIT博士后Douglas Lanman； http://web.media.mit.edu/~dlanman/
(4)opencv中文網(wǎng)站； http://www.opencv.org.cn/index.php/%E9%A6%96%E9%A1%B5
(5)Stanford大學(xué)vision實(shí)驗(yàn)室； http://vision.stanford.edu/research.html
(6)Stanford大學(xué)博士崔靖宇； http://www.stanford.edu/~jycui/
(7)UCLA教授朱松純； http://www.stat.ucla.edu/~sczhu/
(8)中國(guó)人工智能網(wǎng)； http://www.chinaai.org/
(9)中國(guó)視覺(jué)網(wǎng)； http://www.china-vision.net/
(10)中科院自動(dòng)化所； http://www.ia.cas.cn/
(11)中科院自動(dòng)化所李子青研究員； http://www.cbsr.ia.ac.cn/users/szli/
(12)中科院計(jì)算所山世光研究員； http://www.jdl.ac.cn/user/sgshan/
(13)人臉識(shí)別主頁(yè)； http://www.face-rec.org/
(14)加州大學(xué)伯克利分校CV小組； http://www.eecs.berkeley.edu/Research/Projects/CS/vision/
(15)南加州大學(xué)CV實(shí)驗(yàn)室； http://iris.usc.edu/USC-Computer-Vision.html
(16)卡內(nèi)基梅隆大學(xué)CV主頁(yè)；
http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html
(17)微軟CV研究員Richard Szeliski；http://research.microsoft.com/en-us/um/people/szeliski/
(18)微軟亞洲研究院計(jì)算機(jī)視覺(jué)研究組； http://research.microsoft.com/en-us/groups/vc/
(19)微軟劍橋研究院ML與CV研究組； http://research.microsoft.com/en-us/groups/mlp/default.aspx
(20)研學(xué)論壇； http://bbs.matwav.com/
(21)美國(guó)Rutgers大學(xué)助理教授劉青山； http://www.research.rutgers.edu/~qsliu/
(22)計(jì)算機(jī)視覺(jué)最新資訊網(wǎng)； http://www.cvchina.info/
(23)運(yùn)動(dòng)檢測(cè)、陰影、跟蹤的測(cè)試視頻下載； http://apps.hi.baidu.com/share/detail/18903287
(24)香港中文大學(xué)助理教授王曉剛； http://www.ee.cuhk.edu.hk/~xgwang/
(25)香港中文大學(xué)多媒體實(shí)驗(yàn)室（湯曉鷗）; http://mmlab.ie.cuhk.edu.hk/
(26)U.C. San Diego. computer vision;http://vision.ucsd.edu/content/home
(27)CVonline; http://homepages.inf.ed.ac.uk/rbf/CVonline/
(28)computer vision software; http://peipa.essex.ac.uk/info/software.html
(29)Computer Vision Resource; http://www.cvpapers.com/
(30)computer vision research groups;http://peipa.essex.ac.uk/info/groups.html
(31)computer vision center; http://computervisioncentral.com/cvcnews
(32)浙江大學(xué)圖像技術(shù)研究與應(yīng)用（ITRA）團(tuán)隊(duì)：http://www.dvzju.com/
(33)自動(dòng)識(shí)別網(wǎng)：http://www.autoid-china.com.cn/
(34)清華大學(xué)章毓晉教授：http://www.tsinghua.edu.cn/publish/ee/4157/2010/20101217173552339241557/20101217173552339241557_.html
(35)頂級(jí)民用機(jī)器人研究小組Porf.Gary領(lǐng)導(dǎo)的Willow Garage:http://www.willowgarage.com/
(36)上海交通大學(xué)圖像處理與模式識(shí)別研究所：http://www.pami.sjtu.edu.cn/
(37)上海交通大學(xué)計(jì)算機(jī)視覺(jué)實(shí)驗(yàn)室劉允才教授：http://www.visionlab.sjtu.edu.cn/
(38)德克薩斯州大學(xué)奧斯汀分校助理教授Kristen Grauman ：http://www.cs.utexas.edu/~grauman/
(39)清華大學(xué)電子工程系智能圖文信息處理實(shí)驗(yàn)室（丁曉青教授）：http://ocrserv.ee.tsinghua.edu.cn/auto/index.asp
(40)北京大學(xué)高文教授：http://www.jdl.ac.cn/htm-gaowen/
(41)清華大學(xué)艾海舟教授：http://media.cs.tsinghua.edu.cn/cn/aihz
(42)中科院生物識(shí)別與安全技術(shù)研究中心：http://www.cbsr.ia.ac.cn/china/index%20CH.asp
(43)瑞士巴塞爾大學(xué) Thomas Vetter教授：http://informatik.unibas.ch/personen/vetter_t.html
(44)俄勒岡州立大學(xué) Rob Hess博士：http://blogs.oregonstate.edu/hess/
(45)深圳大學(xué) 于仕祺副教授：http://yushiqi.cn/
(46)西安交通大學(xué)人工智能與機(jī)器人研究所：http://www.aiar.xjtu.edu.cn/
(47)卡內(nèi)基梅隆大學(xué)研究員Robert T. Collins:http://www.cs.cmu.edu/~rcollins/home.html#Background
(48)MIT博士Chris Stauffer:http://people.csail.mit.edu/stauffer/Home/index.php
(49)美國(guó)密歇根州立大學(xué)生物識(shí)別研究組(Anil K. Jain教授)：http://www.cse.msu.edu/rgroups/biometrics/
(50)美國(guó)伊利諾伊州立大學(xué)Thomas S. Huang:http://www.beckman.illinois.edu/directory/t-huang1
(51)武漢大學(xué)數(shù)字?jǐn)z影測(cè)量與計(jì)算機(jī)視覺(jué)研究中心：http://www.whudpcv.cn/index.asp
(52)瑞士巴塞爾大學(xué)Sami Romdhani助理研究員：http://informatik.unibas.ch/personen/romdhani_sami/
(53)CMU大學(xué)研究員Yang Wang:http://www.cs.cmu.edu/~wangy/home.html
(54)英國(guó)曼徹斯特大學(xué)Tim Cootes教授：http://personalpages.manchester.ac.uk/staff/timothy.f.cootes/
(55)美國(guó)羅徹斯特大學(xué)教授Jiebo Luo:http://www.cs.rochester.edu/u/jluo/
(56)美國(guó)普渡大學(xué)機(jī)器人視覺(jué)實(shí)驗(yàn)室：https://engineering.purdue.edu/RVL/Welcome.html
(57)美國(guó)賓利州立大學(xué)感知、運(yùn)動(dòng)與認(rèn)識(shí)實(shí)驗(yàn)室：http://vision.cse.psu.edu/home/home.shtml
(58)美國(guó)賓夕法尼亞大學(xué)GRASP實(shí)驗(yàn)室：https://www.grasp.upenn.edu/
(59)美國(guó)內(nèi)達(dá)華大學(xué)里諾校區(qū)CV實(shí)驗(yàn)室：http://www.cse.unr.edu/CVL/index.php
(60)美國(guó)密西根大學(xué)vision實(shí)驗(yàn)室：http://www.eecs.umich.edu/vision/index.html
(61)University of Massachusetts(麻省大學(xué)),視覺(jué)實(shí)驗(yàn)室：http://vis-www.cs.umass.edu/index.html
(62)華盛頓大學(xué)博士后Iva Kemelmacher:http://www.cs.washington.edu/homes/kemelmi
(63)以色列魏茨曼科技大學(xué)Ronen Basri:http://www.wisdom.weizmann.ac.il/~ronen/index.html
(64)瑞士ETH-Zurich大學(xué)CV實(shí)驗(yàn)室：http://www.vision.ee.ethz.ch/boostingTrackers/index.htm
(65)微軟CV研究員張正友：http://research.microsoft.com/en-us/um/people/zhang/
(66)中科院自動(dòng)化所醫(yī)學(xué)影像研究室：http://www.3dmed.net/
(67)中科院田捷研究員：http://www.3dmed.net/tian/
(68)微軟Redmond研究院研究員Simon Baker:http://research.microsoft.com/en-us/people/sbaker/
(69)普林斯頓大學(xué)教授李凱：http://www.cs.princeton.edu/~li/
(70)普林斯頓大學(xué)博士賈登：http://www.cs.princeton.edu/~jiadeng/
(71)牛津大學(xué)教授Andrew Zisserman： http://www.robots.ox.ac.uk/~az/
(72)英國(guó)leeds大學(xué)研究員Mark Everingham:http://www.comp.leeds.ac.uk/me/
(73)英國(guó)愛(ài)丁堡大學(xué)教授Chris William: http://homepages.inf.ed.ac.uk/ckiw/
(74)微軟劍橋研究院研究員John Winn: http://johnwinn.org/
(75)佐治亞理工學(xué)院教授Monson H.Hayes：http://savannah.gatech.edu/people/mhayes/index.html
(76)微軟亞洲研究院研究員孫劍：http://research.microsoft.com/en-us/people/jiansun/
(77)微軟亞洲研究院研究員馬毅：http://research.microsoft.com/en-us/people/mayi/
(78)英國(guó)哥倫比亞大學(xué)教授David Lowe: http://www.cs.ubc.ca/~lowe/
(79)英國(guó)愛(ài)丁堡大學(xué)教授Bob Fisher: http://homepages.inf.ed.ac.uk/rbf/
(80)加州大學(xué)圣地亞哥分校教授Serge J.Belongie:http://cseweb.ucsd.edu/~sjb/
(81)威斯康星大學(xué)教授Charles R.Dyer: http://pages.cs.wisc.edu/~dyer/
(82)多倫多大學(xué)教授Allan.Jepson: http://www.cs.toronto.edu/~jepson/
(83)倫斯勒理工學(xué)院教授Qiang Ji: http://www.ecse.rpi.edu/~qji/
(84)CMU研究員Daniel Huber: http://www.ri.cmu.edu/person.html?person_id=123
(85)多倫多大學(xué)教授：David J.Fleet: http://www.cs.toronto.edu/~fleet/
(86)倫敦大學(xué)瑪麗女王學(xué)院教授Andrea Cavallaro:http://www.eecs.qmul.ac.uk/~andrea/
(87)多倫多大學(xué)教授Kyros Kutulakos: http://www.cs.toronto.edu/~kyros/
(88)杜克大學(xué)教授Carlo Tomasi: http://www.cs.duke.edu/~tomasi/
(89)CMU教授Martial Hebert: http://www.cs.cmu.edu/~hebert/
(90)MIT助理教授Antonio Torralba: http://web.mit.edu/torralba/www/
(91)馬里蘭大學(xué)研究員Yasel Yacoob: http://www.umiacs.umd.edu/users/yaser/
(92)康奈爾大學(xué)教授Ramin Zabih: http://www.cs.cornell.edu/~rdz/
(93)CMU博士田淵棟: http://www.cs.cmu.edu/~yuandong/
(94)CMU副教授Srinivasa Narasimhan: http://www.cs.cmu.edu/~srinivas/
(95)CMU大學(xué)ILIM實(shí)驗(yàn)室：http://www.cs.cmu.edu/~ILIM/
(96)哥倫比亞大學(xué)教授Sheer K.Nayar: http://www.cs.columbia.edu/~nayar/
(97)三菱電子研究院研究員Fatih Porikli ：http://www.porikli.com/
(98)康奈爾大學(xué)教授Daniel Huttenlocher：http://www.cs.cornell.edu/~dph/
(99)南京大學(xué)教授周志華：http://cs.nju.edu.cn/zhouzh/index.htm
(100)芝加哥豐田技術(shù)研究所助理教授Devi Parikh: http://ttic.uchicago.edu/~dparikh/index.html
(101)瑞士聯(lián)邦理工學(xué)院博士后Helmut Grabner: http://www.vision.ee.ethz.ch/~hegrabne/#Short_CV
(102)香港中文大學(xué)教授賈佳亞：http://www.cse.cuhk.edu.hk/~leojia/index.html
(103)南洋理工大學(xué)副教授吳建鑫：http://c2inet.sce.ntu.edu.sg/Jianxin/index.html
(104)GE研究院研究員李關(guān)：http://www.cs.unc.edu/~lguan/
(105)佐治亞理工學(xué)院教授Monson Hayes:http://savannah.gatech.edu/people/mhayes/
(106)圖片檢索國(guó)際會(huì)議VOC(微軟劍橋研究院組織): http://pascallin.ecs.soton.ac.uk/challenges/VOC/
(107)機(jī)器視覺(jué)開(kāi)源處理庫(kù)匯總：http://archive.cnblogs.com/a/2217609/
(108)布朗大學(xué)教授Benjamin Kimia: http://www.lems.brown.edu/kimia.html
(109)數(shù)據(jù)堂-圖像處理相關(guān)的樣本數(shù)據(jù)：http://www.datatang.com/data/list/602026/p1
(110)東軟基于CV的汽車(chē)輔助駕駛系統(tǒng)：http://www.neusoft.com/cn/solutions/1047/
(111)馬里蘭大學(xué)教授Rema Chellappa:http://www.cfar.umd.edu/~rama/
(112)芝加哥豐田研究中心助理教授Devi Parikh：http://ttic.uchicago.edu/~dparikh/index.html
(113)賓夕法尼亞大學(xué)助理教授石建波：http://www.cis.upenn.edu/~jshi/
(114)比利時(shí)魯汶大學(xué)教授Luc Van Gool：http://www.vision.ee.ethz.ch/members/get_member.cgi?id=1, http://www.vision.ee.ethz.ch/~vangool/
(115)行人檢測(cè)主頁(yè)：http://www.pedestrian-detection.com/
(116)法國(guó)學(xué)習(xí)算法與系統(tǒng)實(shí)驗(yàn)室Basilio Noris博士：http://lasa.epfl.ch/people/member.php?SCIPER=129576 http://mldemos.epfl.ch/
轉(zhuǎn)自:http://blog.csdn.net/carson2005
* Indirect access: (General, but inefficient, access to any type image)
效率低！o
For a single-channel byte image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
CvScalar s;
s=cvGet2D(img,i,j); // get the (i,j) pixel value
printf("intensity=%f/n",s.val[0]);
s.val[0]=111;
cvSet2D(img,i,j,s); // set the (i,j) pixel value
o For a multi-channel float (or byte) image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
CvScalar s;
s=cvGet2D(img,i,j); // get the (i,j) pixel value
printf("B=%f, G=%f, R=%f/n",s.val[0],s.val[1],s.val[2]);
s.val[0]=111;
s.val[1]=111;
s.val[2]=111;
cvSet2D(img,i,j,s); // set the (i,j) pixel value
* Direct access: (Efficient access, but error prone)o For a single-channel byte image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
((uchar *)(img->imageData + i*img->widthStep))[j]=111;
o For a multi-channel byte image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 0]=111; // B
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 1]=112; // G
((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels + 2]=113; // R
o For a multi-channel float image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 0]=111; // B
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 1]=112; // G
((float *)(img->imageData + i*img->widthStep))[j*img->nChannels + 2]=113; // R
* Direct access using a pointer: (Simplified and efficient access under limiting assumptions)o For a single-channel byte image:IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(uchar);
uchar* data = (uchar *)img->imageData;
data[i*step+j] = 111;
o For a multi-channel byte image:IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(uchar);
int channels = img->nChannels;
uchar* data = (uchar *)img->imageData;
data[i*step+j*channels+k] = 111;
o For a multi-channel float image (assuming a 4-byte alignment):IplImage* img = cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
int height = img->height;
int width = img->width;
int step = img->widthStep/sizeof(float);
int channels = img->nChannels;
float * data = (float *)img->imageData;
data[i*step+j*channels+k] = 111;
* Direct access using a c++ wrapper: (Simple and efficient access)o Define a c++ wrapper for single-channel byte images, multi-channel byte images, and multi-channel float images:template<class T> class Image
{
private:
IplImage* imgp;
public:
Image(IplImage* img=0) {imgp=img;}
~Image(){imgp=0;}
void operator=(IplImage* img) {imgp=img;}
inline T* operator[](const int rowIndx) {
return ((T *)(imgp->imageData + rowIndx*imgp->widthStep));}
};
typedef struct{
unsigned char b,g,r;
} RgbPixel;
typedef struct{
float b,g,r;
} RgbPixelFloat;
typedef Image<RgbPixel> RgbImage;
typedef Image<RgbPixelFloat> RgbImageFloat;
typedef Image<unsigned char> BwImage;
typedef Image<float> BwImageFloat;
o For a single-channel byte image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
BwImage imgA(img);
imgA[i][j] = 111;
o For a multi-channel byte image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
RgbImage imgA(img);
imgA[i][j].b = 111;
imgA[i][j].g = 111;
imgA[i][j].r = 111;
o For a multi-channel float image:IplImage* img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
RgbImageFloat imgA(img);
imgA[i][j].b = 111;
imgA[i][j].g = 111;
imgA[i][j].r = 111;
最近在做ruoyuYang的作業(yè)，搜集了一些關(guān)于各種細(xì)分算法的介紹。
——————————————————————————————————————————————————隨著Directx11的推出，細(xì)分曲面在游戲中得到了越來(lái)越大的關(guān)注。偶一開(kāi)始覺(jué)得是一大堆復(fù)雜數(shù)學(xué)推導(dǎo)的東西，因?yàn)閷?dǎo)師在中科院的博士幾年就是在做細(xì)分曲面，聽(tīng)說(shuō)一個(gè)很強(qiáng)的師兄三年也都是在做細(xì)分曲面。近來(lái)做了幾天助教幫忙改作業(yè)才偶然看到原來(lái)細(xì)分曲面也有很簡(jiǎn)單的算法實(shí)現(xiàn)， 比如Catmull-Clark Subdivision算法，其可以對(duì)任意拓?fù)浣Y(jié)構(gòu)的多邊形進(jìn)行細(xì)分。下面簡(jiǎn)要介紹下。
細(xì)分新的曲面，先求出新的曲面的頂點(diǎn)：
Face point（位于原來(lái)多邊形面里的新頂點(diǎn)）
Edge point（在原來(lái)的邊中點(diǎn)附近的新頂點(diǎn)）
New vertex point （對(duì)原來(lái)的頂點(diǎn)進(jìn)行調(diào)整得到新頂點(diǎn)）
Face point：
給定一個(gè)面F，有頂點(diǎn)V1,V2,……，Vn，那么新的Face point，VF計(jì)算公式如下
Edge point:
假設(shè)一邊E的兩個(gè)頂點(diǎn)為v和w，還有相鄰的兩個(gè)面為F1和F2（其面頂點(diǎn)已經(jīng)算出為VF1和VF2）。那么對(duì)應(yīng)這個(gè)邊的新頂點(diǎn)VE為
New Vertex point:
給定一個(gè)頂點(diǎn)v。假設(shè)Q是與v相鄰的多邊形的face point的平均值；v與n條邊相鄰，R是與v相鄰的邊的中點(diǎn)的平均值，那么調(diào)整后得到的新頂點(diǎn)位置v'為。
得到新的頂點(diǎn)后，邊是如何產(chǎn)生？
1：每個(gè)面頂點(diǎn)（Face Point）VF與包圍它的邊對(duì)應(yīng)的邊頂點(diǎn)(Edge Point)VE相連。
2：每個(gè)頂點(diǎn)調(diào)整后得到的新頂點(diǎn)（new vertex point）v’與它相鄰的邊上的點(diǎn)（edge point）VE相連。
細(xì)分結(jié)果示例可以看下圖
轉(zhuǎn)自:
http://blog.csdn.net/qiul12345/article/details/5938771
一. 圖形學(xué)、可視化領(lǐng)域的會(huì)議：
(一)高級(jí)別會(huì)議
1. Siggraph (圖形學(xué)領(lǐng)域最高級(jí)別會(huì)議，不知SCI收錄否。國(guó)內(nèi)研究者除非結(jié)果特
牛，輕易別投)
2. Eurograph (作為Computer Graphics Forum一期發(fā)表，SCI收錄，影響不斷增長(zhǎng)
3. IEEE proceeding of Visualization (可視化領(lǐng)域最高級(jí)別會(huì)議，EI收錄，聲譽(yù)
很好)
4. IEEE Symposium of Volume visualization(會(huì)議3的一個(gè)伴隨的會(huì)議，EI收錄，
聲譽(yù)很好)
(二)一般的會(huì)議
1. Pacific Graphics(EI收錄)
2. CGI: Computer Graphics International (EI是否收錄不清楚)
3. WSCG: Int.Conf.on Computer Graphics, Visualization and Computer
Vision
4. Rendering
5. Visualization and Data Analysis----SPIE Electronic Imaging系列會(huì)議之一
(EI收錄，容易接受)
6. Visualization, Image-Guided Procedures, and Display-----SPIE Medical
Imaging系列會(huì)議之一 (EI收錄，容易接受)
7.Joint Eurographics - IEEE TCVG Symposium on Visualization (估計(jì)EI收錄)
二. 三維醫(yī)學(xué)圖像的可視化與分析的會(huì)議
(一)高級(jí)別會(huì)議
1. MICCAI----Medical Image Computing and Computer-Assisted Intervention
(醫(yī)學(xué)圖像的計(jì)算與分析領(lǐng)域最高級(jí)別會(huì)議，Springer出版，論文(Oral,Poster)
被SCI收錄，聲譽(yù)相當(dāng)好. 不過(guò)國(guó)內(nèi)研究者似乎未發(fā)表過(guò)。特別今年在日本召
開(kāi)，但國(guó)內(nèi)無(wú)人投中. MICCAI接受的論文數(shù)很多，長(zhǎng)文超過(guò)100篇，短文也有
100篇，短文可能不被SCI收錄。也接受醫(yī)學(xué)可視化的論文)
2. IPMI----Information processing in Medical imaging (醫(yī)學(xué)圖像分析領(lǐng)域非
常有影響受尊重的會(huì)議，屬于Workshop。許多新結(jié)果先在這里報(bào)告。Springer出
版，估計(jì)被SCI收錄。但接受論文很少，約40篇左右吧)
3. CVPR-----Computer Vision & Pattern Recognition(屬于計(jì)算機(jī)視覺(jué)領(lǐng)域的兩
個(gè)最高級(jí)別會(huì)議中的一個(gè)。有一個(gè)專題是醫(yī)學(xué)圖像分析。基于圖像分析的思路處理
三維醫(yī)學(xué)圖像的特別有意義的結(jié)果可以投這個(gè)會(huì)議。該會(huì)議聲譽(yù)非常好，EI收錄，但很
不好投)
4. ICCV----IEEE International Conference on Computer Vision(計(jì)算機(jī)視覺(jué)領(lǐng)
域的兩個(gè)最高級(jí)別會(huì)議中的另一個(gè)。今年在北京召開(kāi)。EI收錄。三維醫(yī)學(xué)圖像分析的很好
結(jié)果可以投這個(gè)會(huì)議。不好投)
注： 在上述幾個(gè)會(huì)議中，每年都有各個(gè)方向的牛人參加，報(bào)告各個(gè)領(lǐng)域的最新進(jìn)展
。因此，這樣的會(huì)很有意義。在同行的眼中，這些會(huì)議發(fā)表的論文不比低級(jí)別的外文期
刊的論文差。
(二)一般的會(huì)議
1. Medicai imaging----SPIE舉辦的系列會(huì)議，共7個(gè)，主題分別是：
Visualization, Image-Guided Procedures, and Display
Physics of Medical Imaging
Physiology and Function: Methods, Systems, and Applications
Image Processing
PACS and Integrated Medical Information Systems: Design and Evalua
tion
Image Perception, Observer Performance, and Technology Assessment
Ultrasonic Imaging and Signal Processing
(SPIE會(huì)議相對(duì)容易接受，而且EI收錄。不過(guò)EI收錄的慢，因?yàn)闀?huì)議論文集在會(huì)
議10個(gè)月后才能出版)
2. CARS------Computer Aided Radiology and Surgery: 分多個(gè)不同的主題會(huì)議