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1、P1:IML/FFXP2:IML/FFXQC:IML/FFXT1:IMLMOBK039-FMMOBK039-Median.clsNovember9,200621:41TensorVotingAPerceptualOrganizationApproachtoComputerVisionandMachineLearningiP1:IML/FFXP2:IML/FFXQC:IML/FFXT1:IMLMOBK039-FMMOBK039-Median.clsNovember9,200621:41Copyright©2006byMorgan&ClaypoolAllrightsreserved.Nopart
2、ofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedinanyformorbyanymeansÑelectronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotationsinprintedreviews,withoutthepriorpermissionofthepublisher.TensorVoting:APerceptualOrganizationApproachtoComputerVisionandMachineLea
3、rningPhilipposMordohaiandGerardMedioni«www.morganclaypool.comISBN:1598291009paperbackISBN:15982910099781598291001paperbackISBN:1598291017ebookISBN:15982910179781598291018ebookDOI:10.2200/S00049ED1V01Y200609IVM008APublicationintheMorgan&ClaypoolPublishersSeries:SYNTHESISLECTURESONIMAGE,VIDEO,ANDMULT
4、IMEDIAPROCESSINGLecture#8SeriesEditor:AlanC.Bovik,UniversityofTexas,AustinISSNPrint1559-8136Electronic1559-8144FirstEdition10987654321iiP1:IML/FFXP2:IML/FFXQC:IML/FFXT1:IMLMOBK039-FMMOBK039-Median.clsNovember9,200621:41TensorVotingAPerceptualOrganizationApproachtoComputerVisionandMachineLearningPhi
5、lipposMordohaiUniversityofNorthCarolinaGerardMedioni´UniversityofSouthernCaliforniaSYNTHESISLECTURESONIMAGE,VIDEO,ANDMULTIMEDIAPROCESSING#8MMorgan&ClaypoolPublishers&CiiiP1:IML/FFXP2:IML/FFXQC:IML/FFXT1:IMLMOBK039-FMMOBK039-Median.clsNovember9,200621:41ivABSTRACTThislecturepresentsresearchonagenera
6、lframeworkforperceptualorganizationthatwasconductedmainlyattheInstituteforRoboticsandIntelligentSystemsoftheUniversityofSouthernCalifornia.Itisnotwrittenasahistoricalrecountofthework,sincethesequenceofthepresentationisnotinchronologicalorder.Itaimsatpresentinganapproachtoawiderangeofproblemsincompu
7、tervisionandmachinelearningthatisdata-driven,localandrequiresaminimalnumberofassumptions.ThetensorvotingframeworkcombinesthesepropertiesandprovidesauniÞedperceptualorganizationmethodologyapplicableinsituati
