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1、DOTTORATODIRICERCAININGEGNERIADELL’INFORMAZIONEXIVCICLOSedeAmministrativaUniversit`adegliStudidiMODENAeREGGIOEMILIATESIPERILCONSEGUIMENTODELTITOLODIDOTTOREDIRICERCAInteractiveConstraintSatisfactionProblemsforArtificialVisionRelatore:Prof.CesareStefanelliCorrelato
2、re:Prof.PaolaMelloCANDIDATOMarcoGavanelliACKNOWLEDGMENTSIwouldliketothankallthosepeoplewhomadethisthesispossibleandanenjoyableexperienceforme.Inparticular,IwishtothankRitaCucchiara,EvelinaLamma,PaolaMello,MassimoPiccardi,andCesareStefanelliforthecontinuoussuppor
3、tinallphasesofthiswork.IalsowishtothankCarmenGervetforvaluablesuggestionsandhelpduringmyvisitinIC-Parc.AspecialthankgoestoMichelaMilano,whohasalwaysencouragedmeduringmystudies,guidingmyworkandhelpingwheneverIwasinneed.iiABSTRACTInteractiveConstraintSatisfactionP
4、roblemsforArtificialVisionMarcoGavanelli,Ph.D.Universit`adegliStudidiFerraraArtificialVisionisanimportantfieldofArtificialIntelligence:thehumanbrainisabletoderivevarioustypesofinformationabouttheouterworldfromvision.However,thesemanticinterpretationofobjectsisahardt
5、askforacomputer.Constraintshavebeenwidelyusedforvisualrecognition,becausetheyareabletodescribeverycomplexmodelsandsituationsinanaturalway[115,86]∗.ConstraintLogicProgramming[67]isanewparadigmofdeclarativeprogramminglan-guagesthatisabletodealdeclarativelyandefficie
6、ntlywithproblemsdescribedwithcon-straints.Inthisthesis,weaddressedproblemsthatstemfromArtificialVisionwithconstraints.Wedevelopeda3Dvisualsearchsystemabletodetectanobjectdescribedwithconstraintsinanimage.WeprovideconstraintmodelsfordealingwiththeproblemsinArtifici
7、alVision.WegeneralizetheappliedtechniquestootherimportantfieldsofArtificialIntel-ligence,developingnewtoolsofConstraintSatisfactionandOptimizationinConstraintLogicProgramming.Inordertoobtainefficiency,weproposeatightinteractionbetweentheConstraintSolverandtheprovide
8、rofvisualfeatures.Wegiveatheoreticalmodel,solvingalgorithmandalanguageextension.∗Bracketedreferencesplacedsuperiortothelineoftextrefertothebibliography.iiiWemodel3Dob
