模式识别论文Pattern recognitionWord下载.docx

模式识别论文Pattern recognitionWord下载.docx

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Sparserepresentationoffacerecognitiontechnologyhasbeenextensivelystudied.Facerecognitionbasedonsparserepresentationistheconstructionofwordsusingtrainingpictures

Thesparselinearcombinationcoefficientsandexergyexergycodebysolvinganunderdeterminedequationtoobtainthetestimagesaccordingtothesecoefficients

Theimagerecognitionclassification.

KeywordsimageprocessinginthesparserepresentationoftheMPwithinthegeneticalgorithmofsparsedecomposition

Face,recognition,via,sparse,representation

Abstract:

sparse,representation,of,images,is,very,suitable,,for,image,processing,

But,the,computational,burden,in,sparse,decomposition,process,image,is,huge,,A,new

Fast,algorithm,was,presented,based,on,Matching,Pursuit（MP）,image,sparse

Decomposition.At,first,Genetic,Algorithms（GA）,was,applied,to,effectively,search

In,the,dictionary,of,atoms,for,the,best,atom,at,each,,step,of,MP

Face,recognition,problem,is,a,classic,problem,of,pattern,,recognition.,In,recent

Years,inspired,by,the,theory,of,perception,is,compressed,sparse

Representation-based,face,recognition,technology,has,been,widely,studied.,Face

Recognition,based,on,sparse,representation,is,to,take,advantage,,of,the,training

Images,constructed,dictionary,owed,by,solving,a,the,most,,sparse,linear,combination

Coefficients,given,equation,to,obtain,the,test,images,then,these,coefficients,to

Identifyimageclassification.

Keywords:

imageprocessing;

sparserepresentation;

sparsedecomposition;

MatchingPursuit;

GeneticAlgorithms

0Introductionthecurrentfacerecognitiontechnologyofrapiddevelopmentespeciallytheexergybased

Staticfacedetectionandrecognition,andfacefeatureextraction

Multifacerecognitionbasedonmultiposehasbeenachieved

Agreatdealofresearch.Buttheexergyexergyinmorecomplexenvironments

Suchasfacialexpressionrecognition,illuminationcompensationandGuangZhaomo

Theestablishmentofthemodel,thetreatmentofagechanges,andavarietyoftestingdata

Thereisalackofeffectivemethodsforfusion.

Facerecognitionincludesthreestepsinfacedetection

Measurement,facefeatureextraction,facerecognitionandverification.Thereare

Peopleonthis

Extensionoftheexergybasedontheabovethreesteps

OnExergyincreasedearlystandardization,andcorrectionandlaterpoints

Classandmanagementthesetwosteps.

Theresearchoffacerecognitionstartedinthelate1960s

L2].Hasexperienced40yearsofdevelopment.Roughlydividedintothree

Threestages:

Thefirststageistheinitialstagefrom60stotheendofexergy

Late80s.Themaintechniqueadoptedatthattimewasbase

Tosetthestructurecharacteristicsofthefacerecognitionmethodofexergyis

Asageneralpatternrecognitionproblemisstudied.generation

ThefiguresincludeBledsoe（Bledsoe）andGordonStein

（Goldstein）,Harmon（Harmon）,andKimWuHsiung

（KanadeTakeo）etal.Atthattimealmostallwereidentified

Theprocessreliesonmanualoperationandresultsinnoexergyintoveryimportantpracticalapplicationsinnotmanybasicallyno

Havepracticalapplication.

Thesecondstageisintheexplorationstagefrom70stoeight

Thetenage.Duringthisperiod,aswellasengineersinthesmoke

Leadneuroscientistsandpsychologiststothefield

Research.Theformerismainlythroughtheperceptionmechanismofthehumanbrain

Toexplorethepossibilityinautomaticfacerecognitionwhiletheorder

Sometheoreticalobtainedhassomedefectsandpartialnaturebutin

Engineeringtechniquesfordesignandimplementationofalgorithmsandsystems

Thepersonnelhavetheimportanttheoryinstructionsignificance.

Thethirdstageisthestageofrapiddevelopmentinthelastcenturyfromthenine

Fromthetentothepresent.Computervisionandpatternrecognitiontechnology

Intherapiddevelopmentofcomputerimageprocessingtechnologyanddrives

Therapiddevelopmentoffacerecognition.Governmentsarealsoheavilyfinanced

Inthestudyoffacerecognitionandachievedfruitfulresults.

Amongthem,EigenfaeeandFisherfaceisthismoment

Themostrepresentative,themostsignificantachievementsof