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1、DOTTORATODIRICERCAININGEGNERIADELL’INFORMAZIONEXIVCICLOSedeAmministrativaUniversit`adegliStudidiMODENAeREGGIOEMILIATESIPERILCONSEGUIMENTODELTITOLODIDOTTOREDIRICERCAInteractiveConstraintSatisfactionProblemsforArtificialVisionRelatore:Prof.CesareStefanelliCorrelatore:Prof.Paola
2、MelloCANDIDATOMarcoGavanelliwww.aibbt.com让未来触手可及ACKNOWLEDGMENTSIwouldliketothankallthosepeoplewhomadethisthesispossibleandanenjoyableexperienceforme.Inparticular,IwishtothankRitaCucchiara,EvelinaLamma,PaolaMello,MassimoPiccardi,andCesareStefanelliforthecontinuoussupportinall
3、phasesofthiswork.IalsowishtothankCarmenGervetforvaluablesuggestionsandhelpduringmyvisitinIC-Parc.AspecialthankgoestoMichelaMilano,whohasalwaysencouragedmeduringmystudies,guidingmyworkandhelpingwheneverIwasinneed.iiwww.aibbt.com让未来触手可及ABSTRACTInteractiveConstraintSatisfaction
4、ProblemsforArtificialVisionMarcoGavanelli,Ph.D.Universit`adegliStudidiFerraraArtificialVisionisanimportantfieldofArtificialIntelligence:thehumanbrainisabletoderivevarioustypesofinformationabouttheouterworldfromvision.However,thesemanticinterpretationofobjectsisahardtaskforacompu
5、ter.Constraintshavebeenwidelyusedforvisualrecognition,becausetheyareabletodescribeverycomplexmodelsandsituationsinanaturalway[115,86]∗.ConstraintLogicProgramming[67]isanewparadigmofdeclarativeprogramminglan-guagesthatisabletodealdeclarativelyandefficientlywithproblemsdescribed
6、withcon-straints.Inthisthesis,weaddressedproblemsthatstemfromArtificialVisionwithconstraints.Wedevelopeda3Dvisualsearchsystemabletodetectanobjectdescribedwithconstraintsinanimage.WeprovideconstraintmodelsfordealingwiththeproblemsinArtificialVision.Wegeneralizetheappliedtechniq
7、uestootherimportantfieldsofArtificialIntel-ligence,developingnewtoolsofConstraintSatisfactionandOptimizationinConstraintLogicProgramming.Inordertoobtainefficiency,weproposeatightinteractionbetweentheConstraintSolverandtheproviderofvisualfeatures.Wegiveatheoreticalmodel,solvingal
8、gorithmandalanguageextension.∗Bracketedreferencesplacedsuperiortothelineoft