Final Program WVC2015 v2
Transcrição
Final Program WVC2015 v2
XIWorkshopdeVisãoComputacional WVC´2015 October05th–07th,2015 SãoCarlos–SP-Brazil Program UniversityofSãoPaulo SãoCarlosSchoolofEngineering XIWorkshopdeVisãoComputacional-October05th–07th,2015 2 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Summary WelcometoWVC2015..................................................................................................5 GeneralInformation......................................................................................................6 AuthorandPresenterInformation................................................................................7 OralPresenters..........................................................................................................7 PosterPresenters......................................................................................................7 Committees....................................................................................................................8 OrganizingCommittee..............................................................................................8 SteeringCommittee..................................................................................................8 WorkTeam................................................................................................................9 ScientificCommittee.................................................................................................9 Keynote1.....................................................................................................................12 Keynote2.....................................................................................................................14 Keynote3.....................................................................................................................16 OralSession1...............................................................................................................18 OralSession2...............................................................................................................19 OralSession3...............................................................................................................20 OralSession4...............................................................................................................21 OralSession5...............................................................................................................22 PosterSession1...........................................................................................................24 PosterSession2...........................................................................................................28 UsefulPhoneNumbers................................................................................................32 Annotations..................................................................................................................33 3 XIWorkshopdeVisãoComputacional-October05th–07th,2015 4 XIWorkshopdeVisãoComputacional-October05th–07th,2015 WelcometoWVC2015 TheSãoCarlosSchoolofEngineering,attheUniversityofSãoPaulo(EESC/USP), has the pleasure to welcome you to the XI Workshop on Computer Vision (WVC 2015)andtothecityofSãoCarlos. After four consecutive editions outside the state of São Paulo (Curitiba-PR in 2011,Goiânia-GOin2012,RiodeJaneiro-RJin2013andUberlândia-MGin2014)this edition of the WVC will be held again at the city of São Carlos-SP. The academic, technologicandindustrialforceofSãoCarlosconferredtothecitythetitleof"Capital ofTechnology"inBrazil.TheUniversityofSãoPaulo(USP),theFederalUniversityof São Carlos (UFSCar) and the Brazilian Agricultural Research Corporation (Embrapa) arerecognizedfortheirexcellenceinteachingandresearch,makingthecityapoleof scientific and technological development. São Carlos has a great concentration of scientistsandresearchers,approximatelyonePhDforevery180inhabitants. WVC2015wasplannedverycarefullybytheOrganizingCommittee,whichsought toprovidetheparticipantswithacompletescientificprogram,withseverallectures, oralsessionsandposterpresentations.Wehopethateveryonecantakeadvantageof the activities offered by this event, broadening their horizons through the rich scientificexchangeofexperiencesamongtheparticipants. I would like to thank the WVC Steering Committee for trusting our team and approvingourproposalfororganizingtheWVC2015inSãoCarlos.Iwouldalsoliketo thankallthestudentsfromtheLaboratoryofComputerVision(LAVI)whohavebeen workingsohardplanningandorganizingthiseventsincetheearlybeginning. IamalsogratefultotheDepartmentofElectricalandComputerEngineering,the São Carlos School of Engineering, FAPESP, CAPES and all ours sponsors for the financialandoperationalsupport. Finally, I would like to thank all the authors who submitted their work for this eventandallthereviewerswhosacrificedpartoftheirtimetoevaluatemorethan 100paperssubmittedtotheworkshop. IhopethatyouenjoyWVC2015andthatweallhaveagreatworkshop. MarceloAndradedaCostaVieira ChairofWVC2015 5 XIWorkshopdeVisãoComputacional-October05th–07th,2015 GeneralInformation • • • • • 6 • Yourbadgeispersonalandnottransferable.Pleaseuseyourbadgetoaccess allactivitiesoftheworkshop. Please turn off your mobile phones or switch them to silent/vibrate mode duringallscientificactivities. Allcertificateswillbesentviae-mailaftertheconference. TheWVC2015proceedingswillbepublishedonlinesoonaftertheworkshop. Only papers presented during the workshop will be published in the final versionoftheproceedings. The ticket for the Conference Dinner must be purchased at the event’s office. Ifyouneedaregistrationreceiptpleaserefertotheevent’soffice. XIWorkshopdeVisãoComputacional-October05th–07th,2015 AuthorandPresenterInformation OralPresenters • • • • Eachoralpresentationwillhave15minutes+5minutesforquestions. YourpresentationcanbeinPortuguese,butyourslidesshouldbewrittenin English. Please refer to the workshop program to check the day and time of your presentation. Please make sure to upload your presentation to the computer in the meetingroomonthedayofyourpresentation.Thebesttimeisbeforethe firstsessionofthedayorduringbreaks. PosterPresenters • • • • • • • • Posterspresentationsarehard-copy(paper/poster)formatonly. YourpresentationcanbeinPortuguese,butyourpostershouldbewrittenin English. Poster dimensions should not exceed 180 cm (approx. 70 inch) high x 200 cm(80inch)wide. Pleasehangyourposterinthepanelwiththesamenumberprovidedbythe WVC2015program. Pushpinswillbeprovidedtohangyourposter. Please refer to the workshop program to check the day and time of your presentation. Postersauthorsarerequiredto1)displaytheposterduringthefirstcoffee break of the day of your session 2) attend the Poster Session to answer questions. Remember that during your poster presentation you will have the opportunity to discuss your research with more details. Thus, prepare the best poster you possibly can, aiming at both attracting attention of the readersandhavingenoughmaterialtoanswertheirquestions. 7 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Committees OrganizingCommittee MarceloAndradedaCostaVieira EESC/USP ChairofWVC2015 EvandroLuisLinhariRodrigues SteeringCommitteeChair EESC/USP AdilsonGonzaga EESC/USP MaximiliamLuppe EESC/USP ValdirGrassiJunior EESC/USP MauricioCunhaEscarpinati FACOM/UFU SteeringCommittee EvandroLuisLinhariRodrigues EESC/USP SteeringCommitteeChair AdilsonGonzaga EESC/USP AparecidoNilceuArana FC/UNESP InêsAparecidaGasparotoBoaventura IBILCE/UNESP MaurílioBoaventura IBILCE/UNESP MaurícioMarengoni MACKENZIE/SP LuizAntonioPereiraNeves UFPR MarcoAntônioPiteri FCT/UNESP 8 XIWorkshopdeVisãoComputacional-October05th–07th,2015 WorkTeam MarceloAndradedaCostaVieira EESC/USP ChairofWVC2015 EvandroLuisLinhariRodrigues EESC/USP SteeringCommitteeChair AdilsonGonzaga EESC/USP MaximiliamLuppe EESC/USP ValdirGrassiJunior EESC/USP HelderCesarR.deOliveira EESC/USP LucasRodriguesBorges EESC/USP PolyanaFerreiraNunes EESC/USP TamirisNegri EESC/USP RaissaTavares EESC/USP CarolinaToledo EESC/USP ScientificCommittee AdilsonGonzaga AlessandraAparecidaPaulino AlexAffonso AnaCláudiaMartinez AndersonSoares AndreBindilatti AndréBackes AndréMartins AnfranseraiDias AnselmoPaiva AntonioMariaTomaseli AntôniodaLuz AntônioApolinário AparecidoNilceuMarana AyltonPagamisse BrunoBarufaldi EESC/USP UNESP EESC/USP UFU UFGO UFSCar UFU EESC/USP UEFS UFMA UNESP IFTO UFBA UNESP UNESP EESC/USP 9 XIWorkshopdeVisãoComputacional-October05th–07th,2015 BrunoMatheus BrunoTravençolo CarlosThomaz CarolinaFerraz CeliaBarcelos CelsoOlivete CésarCastañon ChidambaramChidambaram ClaudioGoes ClodoaldoLima CristinaNaderVasconcelos DanielAbdala DaniloEler DelmarCarvalho DenisSalvadeo EmersonPedrino EvandroL.L.Rodrigues FabrizzioSoares FátimaMedeiros FatimaNunes FlávioBortolozzi GiovaniChiachia GustavoB.Borba HelioPedrini HemersonPistori HomeroSchiabel HugoVieiraNeto IálisPaulaJunior InêsA.G.Boaventura IvanNunesdaSilva JacobScharcanski JacquesFacon JanderMoreira JarbasSáJunior JoãoBatistaNeto JoãoMarar JoãoManuelTavares JoãoPauloPapa JoséAlfredoF.Costa JoséEduardoCastanho 10 EESC/USP UFU FEI EESC/USP UFU UNESP PUC/Peru UDESC UEFS UNICAMP UFF UFU UNESP UEFS UNESP UFSCar EESC/USP UFGO UFCE EACH/USP CESUMAR UNICAMP UTFPR UNICAMP UCDB EESC/USP UTFPR UFC UNESP EESC/USP UFRGS PUCPR UFSCar UFC ICMC/USP UNESP FEUP/Portugal UNESP UFRN UNESP XIWorkshopdeVisãoComputacional-October05th–07th,2015 JoséRobertoNogueira JoséSaito JulioCesarNievola JurandydeAlmeida LeandroOliveira LeonardoBatista LeonardoMatos LucasFerrarideOliveira LucianoLulio LucianoSilva LucioJorge LuizAntonioPereiraNeves MarceloA.C.Vieira MarceloZanchetta MárcioAlexandreMarques MarcoAntônioPiteri MauricioC.Escarpinati MauricioGalo MauricioMarengoni MaurilioBoaventura MaximiliamLuppe MessiasMeneguetiJunior MicheleF.Angelo MoacirPontiJúnior MurilloHomem NelsonMascarenhas OdemirBruno PauloEduardoAmbrósio PauloM.A.Marques RaissaTavaresVieira RicardoFerrari RonaldoCosta SilviaMartiniRodrigues TamirisNegri ThiagoRibeiro ValdineiBelini ValdirGrassiJunior WilliamSchwartz UNESP UFSCar PUCPR UNIFESP UFGO UFPB UFS UFPR EESC/USP UFPR EMBRAPA UFPR EESC/USP UFU UNESP UNESP UFU UNESP Mackenzie UNESP EESC/USP UNESP UEFS ICMC/USP UFSCar UFSCar IFSC/USP UESC FMRP/USP EESC/USP UFSCar UFGO UMC EESC/USP UFU UFSCar EESC/USP UFMG 11 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Keynote1 th Monday-October05 –10:30hto12:00h ComputerVisioninMedicalImagingand Measurements JacobScharcanski,Ph.D. UFRGS-UniversidadeFederaldoRioGrandedoSul InstitutodeInformática,RioGrandedoSul,Brasil http://www.inf.ufrgs.br/~jacobs/ Abstract: In this talk, computer vision in medical imaging and measurements is proposed as a way to facilitate the interpretation of phenomena based on medical imagery, or to make inferences based on models of such phenomena. In order to illustrate this presentation, several modeling issues in medical imaging and measurements are discussed, and illustrated by examples. When modeling imaging measurements, usually we are trying to describe the world (or a real world phenomenon) using one or more images, and reconstruct some of its properties based on imagery data (like shape, texture or color). Actually, this is an ill-posed problemthathumanscanlearntosolveeffortlessly,butcomputeralgorithmsoften arepronetoerrors.Nevertheless,insomecasescomputerscansurpasshumansand helpinterpretimagerymoreaccurately,giventheproperchoiceofmodels,aswewill discuss in this talk. Modeling medical imaging measurements often involves errors, andestimatingtheexpectederrorofamodelcanbeimportantinsomeapplications (e.g.whenestimatingatumorsizeanditspotentialgrowth,orshrinkage,inresponse to treatment). Typically, a model has tuning parameters, and these tuning parametersmaychangethemodelcomplexity.Wewishtominimizemodelingerrors andthemodelcomplexity,inotherwords,togetthe‘bigpicture’weoftensacrifice some of the small details. For example, estimating tumor growth (or shrinkage) in response to treatment requires modeling the tumor shape and size, which can be challenging for real tumors, and simplified models may be justifiable if the predictions obtained are informative (e.g. to evaluate the treatment effectiveness). This issue is closely related to machine learning and pattern recognition, and techniques of these areas can be adapted to resolve problems in medical imaging measurements. To conclude this talk, open problems in medical imaging measurementsandmodelselectionarediscussedinsomedetail. 12 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Short Bio: Jacob Scharcanski is a (Full) Professor in Computer Science at the Federal University of Rio Grande do Sul (UFRGS), Brasil. He holds a cross appointment with the Department of ElectricalEngineeringatUFRGS,andalsoisanAdjunctProfessor withtheDepartmentofSystemsDesignEngineering,Universityof Waterloo, Canada. He authored and co-authored over 150 refereed journal and conference papers, book chapters and books, and delivered over 30 invited presentations worldwide. He serves as an Associate Editor for two journals, and has served on dozens of International Conference Committees. In additiontohisacademicactivities,hehasseveraltechnologytransferstotheprivate sector. Professor Scharcanski is a licensed Professional Engineer (PEO, Canada), SeniorMemberoftheIEEE,MemberofSPIE,andservesasCo-ChairoftheTechnical CommitteeIEEEIMSTC-17(ImagingMeasurementsandSystems). 13 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Keynote2 th Tuesday-October06 –10:30hto12:00h PatchFoveationinNonlocalImageFiltering AlessandroFoi,Ph.D. DepartmentofSignalProcessing TampereUniversityofTechnology,Tampere,Finland http://www.cs.tut.fi/~foi/ Abstract:Whenwegazeascene,ourvisualacuityismaximalatthefixationpoint(imagedby the fovea, the central part of the retina) and decreases rapidly towards the periphery of the visualfield.Thisphenomenonisknownasfoveation.Toformacompleteimageofthescene, the human visual system (HVS) typically processes a multitude of foveated retinal images gathered at different fixation points. In this talk we look at the analogies and connections betweenthisfeatureoftheHVSandmodernnonlocal(NL)imagefilters. NL filters rely on the assumption that natural images contain a large number of mutually similarpatchesatdifferentlocationswithintheimage:similarpatchesarefirstidentified,and then used into adaptive weighted averages or more sophisticated nonlinear shrinkage. Such approachisatthecoreofseveralofthemosteffectiveimagerestorationmethodstodate. Crucial elements in the design of NL filters are the metric or distance used for assessing the patch similarity, and the size of the patch. Large patches guarantee stability of the distance with respect to degradations such as noise; however, the mutual similarity between pairs of patches typically decreases as the patch size grows. Thus, a windowed Euclidean distance is commonly employed to balance these two conflicting aspects, assigning lower weights to pixels far from the patch center. Choosing a metric for patch similarity corresponds to assuming a specific model for describing natural images and their self-similarity: the effectivenessofNLmethodsdependsstronglyonthevalidityofsuchunderlyingmodel. We particularly investigate a different form of self-similarity: the foveated self-similarity. Foveationherecorrespondstoaspatiallyvariantbluroperator,characterizedbyblurkernels whosebandwidthdecreaseswiththespatialdistancefromthepatchcenter.Incontrastwith theconventionalwindowing,whichisonlyspatiallyselectiveandattenuatessharpdetailsand smoothareasinequalway,patchfoveationprovidesselectivityinbothspaceandfrequency, mimickingtheHVSinabilitytoperceivedetailsattheperipheryofthecenterofattention. Throughout the talk, we adopt the image denoising problem as a simple means of assessing the effectiveness of descriptive models for natural images. We show that, in nonlocal image filtering,thefoveatedself-similarityisfarmoreeffectivethantheconventionalwindowedselfsimilarity. To facilitate the use of foveation in nonlocal imaging, we present a general frameworkfordesigningfoveationoperators,i.e.linearoperatorsproducingfoveatedpatches by means of spatially variant blur. Within this framework, several parametrized families of foveation operators are demonstrated, including anisotropic ones. Strikingly, the operators enabling the best denoising performance on complex natural images are the radial ones, in completeagreementwiththeorientationpreferenceoftheHVS. 14 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Short Bio: Alessandro Foi received the M.Sc. degree in Mathematics from the Università degli Studi di Milano, Italy, in 2001, the Ph.D. degree in Mathematics from the Politecnico di Milano in 2005, and the D.Sc.Tech. degree in Signal Processing from Tampere University of Technology, Finland, in 2007. He is currently an Academy Research Fellow with the Academy of Finland, at the Department of Signal Processing, Tampere University of Technology, whereheisalsoAssociateProfessor.Hisresearchinterestsincludemathematicaland statistical methods for signal processing, functional and harmonic analysis, and computational modeling of the human visual system. His recent work focuses on spatially adaptive (anisotropic, nonlocal) algorithms for the restoration and enhancement of digital images, on noise modeling for imaging devices, and on the optimaldesignofstatisticaltransformationsforthestabilization,normalization,and analysisofrandomdata.HeisaSeniorMemberoftheIEEE,MemberoftheImage, Video, and Multidimensional Signal Processing Technical Committee of the IEEE SignalProcessingSociety,andanAssociateEditorfortheIEEETransactionsonImage ProcessingandforthenewIEEETransactionsonComputationalImaging. 15 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Keynote3 th Wednesday-October07 –10:30hto12:00h UsingComputerVisionwithdronesinAgriculture LúcioAndrédeCastroJorge,Ph.D. EMBRAPA-EmpresaBrasileiradePesquisaAgropecuária. SãoCarlos,Brasil. http://lattes.cnpq.br/3036476562950521 Abstract: The use of drones in agriculture increase the use of advanced sensors to evaluate the development of different crops providing additional agricultural knowledgetodealwiththevariabilityinthefieldinordertocontributetoincreased crop yields. The technological development of remote sensing techniques using dronesorUAVs,havebeenimprovingthecropmanagementwithgreaterspatialand temporalresolution.Therefore,themainchallengeinthisareaisthedevelopmentof methodsofprocessingimagesquicklyandaccuratelyworkingwithlargevolumesof multidimensional and temporal data. However, despite the enormous potential of thisremotesensing,theirimplementationinpracticeisverylimited.Thisworkwillbe presented the state of the art at all stages, from image acquisition, processing, segmentation,classificationamongothersforapplicationsinagriculture. 16 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Short Bio: Degree in Electrical Engineering - Electronics and Electrical Engineering at the School of Barretos Engineering (1987); Master's degree in Computational Mathematics and Computer Science at Institute of Mathematics and Computer SciencesattheUniversityofSãoPaulo,ICMC-USP(2001);PhDin Signal Processing and Instrumentation from the School of Engineering, University of São Paulo, SEL-EESC-USP (2011); LatoSensu in image processing from the University of Campinas - Unicamp (1990); LatoSensu in Geografical Information Systems from the Federal University of São Carlos - UFSCar (2005); Researcher at Embrapa Instrumentation since 1990; Professor of Image Processing, Computer Graphics and Artificial Intelligence at UNISEB- Colleges COC since2006.ExperienceinComputerScience,workingonthedevelopmentofimage processingsoftware,embeddedsystems,mobiledevices(PDAs),patternrecognition and intelligence computing, computer graphics and geo-referenced systems. Experience applied in several projects in Agriculture, Precision Agriculture, GIS, agricultural monitoring, remote sensing, study of roots, leaves, plant diseases and deficiencies,developmentofUAV(unmannedaerialvehicle)foragriculturaluse. 17 XIWorkshopdeVisãoComputacional-October05th–07th,2015 OralSession1 th Monday-October05 -14:00hto15:40h Chair:AdilsonGonzaga Co-Chair:MarcoA.Piteri PatternRecognition 1 MakinganImageWorthaThousandVisualWords-Glauco 14h00-14h20 VitorPedrosa,USP;AgmaTraina,ICMC/USP; 2 A Study of Filtering Approaches for Sliding Window 14h20-14h40 Pedestrian Detection - Artur Correia, UFMG; Victor Hugo Melo,UFMG;WilliamSchwartz,UFMG; 3 A Bipartite Graph Model Approach For Discriminant Features Evaluation - Pamela Iupi Peixinho, Centro 14h40-15h00 Universitário da FEI; Paulo Silva Rodrigues, Centro Universitário da FEI; Guilherme Wachs Lopes, Centro UniversitáriodaFEI; 4 LocalMappedPatternforSpoofFingerprintDetection–Inês 15h00-15h20 Boaventura, UNESP; Maurilio Boaventura, UNESP; Rodrigo Contreras,UNESP; 5 Multi-scale Local Mapped Pattern for Image Texture Analysis - Maurilio Boaventura, UNESP; Rodrigo Contreras, 15h20-15h40 UNESP;InêsBoaventura,UNESP; THISPRESENTATIONWASMOVEDTOORALSESSION4 5 Detection and Classification of the Periorbital Wrinkles in 2D Images - Daniel Costa, UFBA; Angelo Duarte, UEFS; 15h20-15h40 Deborah Duarte, Clínica Deborah Duarte; Leizer Schnitman, UFBA; 18 XIWorkshopdeVisãoComputacional-October05th–07th,2015 OralSession2 th Tuesday-October06 -08:20hto10:00h Chair:MarceloA.C.Vieira Co-Chair:MaurílioBoaventura FilteringandRestoration 1 2 Filtering Poisson Noise in Digital Breast Tomosynthesis Using an Interactive Non-Local Means Scheme Based on 08h20-08h40 Stochastic Distances - Andre Bindilatti, UFSCar; Marcelo Vieira, USP; Predrag Bakic, UPENN; Andrew Maidment, UPENN;NelsonMascarenhas,UFSCar; Using SSIM as Convergence Criteria in a Variational 08h40-09h00 Superresolution Bayesian Approach - Thais Nascimento, UFES;EvandroSalles,UFES; 3 A New Prior for Inverse Problems Based Demosaicking - 09h00-09h20 RomárioKeitiFugita,UTFPR;MarceloVictorZibetti,;Daniel Pipa; 4 Evolving Convolutional Kernels Using Evolutionary 09h20-09h40 Computing - José Augusto Stuchi, CPqD; Marcus Angeloni, CPqD;MateusCarniatto;BrunoCereser; 5 Denoising Computed Tomography Projections Using Contextual Filters With Statistical Estimation from a Non09h40-10h00 Local Approach on Anscombe Domain - Vinicius Assis, UNESP; Denis Salvadeo, UNESP; Nelson Mascarenhas, UFSCar;AlexandreLevada,UFSCar; 19 XIWorkshopdeVisãoComputacional-October05th–07th,2015 OralSession3 th Tuesday-October06 -14:00hto15:40h Chair:MauricioCunhaEscarpinati Co-Chair:EvandroLuisLinhariRodrigues MedicalandBiomedicalApplications 1 Using the Non-local Means Algorithm to Denoise Mammogaphic Images Acquired with Reduced Radiation Dose-PolyanaNunes,USP;AndreBindilatti,UFSCar;Helder 14h00-14h20 Oliveira, USP; Lucas Borges, USP; Predrag Bakic, UPENN; Andrew Maidment, UPENN; Nelson Mascarenhas, UFSCar; MarceloA.C.Vieira,USP; 2 Graph Measures for Cell Tissue Classification - Letícia 14h20-14h40 Oliveira,UFABC;FranciscoZampirolli,UFABC; 3 GPU-Optimized Pulmonary Nodule Retrieval Based on 3D 14h40-15h00 MarginSharpnessDescriptors-JoséFerreira,UFAl;Marcelo Oliveira,UFAl; 4 ProposalofLocalAutomaticWeighingAttributetoRetrieve Similar Lung Cancer Nodules - David Jones Lucena, UFAl; 15h00-15h20 Marcelo Oliveira UFAl; Aydano Pomponet, UFAl; José Ferreira,UFAl; 5 AutomaticDetectionofLeukocytesfromIntravitalVideo MicroscopyusingthePhaseCongruencyTechnique- 15h20-15h40 KathianiSouza,UFSCar;BrunoGregóriodaSilva,UFSCar; JulianaCarvalho-Tavares,UFMG;RicardoFerrari,UFSCar; 20 XIWorkshopdeVisãoComputacional-October05th–07th,2015 OralSession4 th Wednesday-October07 -08:20hto10:00h Chair:AparecidoNilceuMarana Co-Chair:InêsA.G.Boaventura FeatureExtraction 1 Combining Wavelets and 2D Gabor Descriptors for Iris Recognition in Noncooperative Environments - Sirlene 08h20-08h40 Peixoto, UFOP; Pedro Silva, UFOP; Alvaro Guarda, UFOP; EduardoLuz,UFOP;DavidMenotti,UFOP; 2 TextureAnalysisUsingLocalFractalDimensionofComplex Networks - Diogo Gonçalves, UFMS; Lucas Silva, UFMS; 08h40-09h00 Reinaldo Felipe Araujo, UFMS; Bruno Machado, UFMS; WesleyGonçalves,UFMS–CPPP; 3 Detection and Classification of the Periorbital Wrinkles in 2D Images - Daniel Costa, UFBA; Angelo Duarte, UEFS; 09h00-09h20 Deborah Duarte, Clínica Deborah Duarte; Leizer Schnitman, UFBA; THISPRESENTATIONWASMOVEDTOORALSESSION1 3 Multi-scale Local Mapped Pattern for Image Texture 09h00-09h20 Analysis - Maurilio Boaventura, UNESP; Rodrigo Contreras, UNESP;InêsBoaventura,UNESP; 4 Multimodal Discriminant Analysis of Biomarkers in 09h20-09h40 Alzheimer’s Disease - Samantha Castro, FEI; Luciano Sanchez;GeraldoBusattoFilho;CarlosThomaz,FEI; 5 ColorTextureClassificationbyaLocalMultiscaleDescriptor 09h40-10h00 -TamirisNegri,EESC/USP;AdilsonGonzaga,EESC/USP; 21 XIWorkshopdeVisãoComputacional-October05th–07th,2015 OralSession5 th Wednesday-October07 -14:00hto15:40h Chair:MauricioMarengoni Co-Chair:LuizA.P.Neves ApplicationsinComputerVision 1 Automated Method for Determining Grid Lines Using 14h00-14h20 MAMA-CDM Phantom Images - Bruno Barufaldi, USP; HomeroSchiabel,USP;LeonardoBatista,UFPB; 2 Shape Aligment Using ASM and SVM in Vehicle Images - 14h20-14h40 Maria Aragão, UFS; Jovan Fernandes Junior, UFS; Leonardo Matos,UFS; 3 Information Theoretic Approaches for Adaptive Wavelet 14h40-15h00 ShrinkageinImageDenoising-AlexandreLevada,UFSCar; 4 Omnidirectional Vision Architecture for Embedded Robot 15h00-15h20 NavigationwithRaspberryPi-AndersonNascimento,UFBA; PauloFarias,UFBA; 5 MaximumResponseFiltersandTextureTechniquesApplied 15h20-15h40 to Classification of Mammographic Breast Mass - Danilo Fistarol,UFMS-CPPP;WesleyGonçalves,UFMS–CPPP; 22 XIWorkshopdeVisãoComputacional-October05th–07th,2015 23 XIWorkshopdeVisãoComputacional-October05th–07th,2015 PosterSession1 th Monday-October05 -15:40hto17:30h Chair: MaximiliamLuppe Co-Chairs: AdilsonGonzaga MarceloA.C.Vieira MauricioCunhaEscarpinati AparecidoNilceuMarana MarcoA.Piteri 24 1. Analysis of Iris Texture Under Pupil Contraction/Dilation for Biometric Recognition-JonesSouza,USP;AdilsonGonzaga,USP;RaissaTavaresVieira, USP; 2. Unconstrained Face Recognition using Weber Local Descriptor and SVM - AlexAffonso,USP;EvandroRodrigues,EESC/USP; 3. Comparison Between Isotropic and Adaptive Pore Detection Methods for Fingerprint Recognition - Murilo Varges da Silva, UNESP/IFSP; João Paulo Luiz,UNESP;MarcusAngeloni,CPqD;AlessandraPaulino,UNESP;Aparecido Marana,UNESP; 4. Wrist Veins Texture Analysis for Biometric Systems - Vitor Barbedo, IFSP; JonesSouza,USP; 5. PerformanceEvaluationof3DTextureAttributesand3DMarginSharpness intheRetrievalof Lung Nodules Similars - Lucas Lima, UFAL; José Ferreira Junior,UFAL;MarceloOliveira,UFAL; 6. Face Recognition with Uniform Local Binary Patterns - Luiz D Amore, Universidade Presbiteriana Mackenzie; Maurício Marengoni, Universidade PresbiterianaMackenzie; 7. Patterns Detection in ECG Signal Applied to Biometric Recognition - Henrique Passos, USP; Daniel Martins da Costa, USP; Sarajane Peres, USP; ClodoaldoLima,USP; 8. IrisRecognitionusingSupportVectorMachineandLeastSquaresSupport Vector Machine: A Comparative Study - Daniel Martins da Costa, USP; HenriquePassos,USP;SarajanePeres,USP;ClodoaldoLima,USP; 9. ComparisonofCharacteristicsofDescriptorsfortheConstructionofDigital ImagesMosaic-DaviFernandes,IFSPBoituva;AndréTarallo,IFSPBoituva; XIWorkshopdeVisãoComputacional-October05th–07th,2015 10. Texture Analysis by Grouping Similar Vertices in Complex Networks - LeonardoScabini,UFMS;WesleyGonçalves,UFMS/CPPP;AmauryCastroJr, UFMS; 11. Improving Image Classification Performance by Descriptor Size Reduction andBag-of-Features-CarolinaFerraz,USP;AdilsonGonzaga,USP; 12. BrazilianLicensePlateCharacterRecognitionusingDeepLearning-Sirlene Peixoto,UFOP;GabrielGonçalves,UFMG;GuillermoCámara-Chávez,UFOP; WilliamSchwartz,UFMG;DavidMenotti,UFOP; 13. Gabor Filter Parameter Optimization for Localization Step of Plate RecognitionSystem-OzgurAltun,ProlineBilisimSistemleri;FarukCanKaya, ProlineBilisimSistemleri;TuranMuratGuvenc,ProlineBilisimSistemleri; 14. EvaluationofTechnicalofImageEnhancementwithObjetivesMetricsand Execution Average Time - Jonas Rodrigues Vieira dos Santos, UFC; Paulo CésarCortez;RodrigoFernandesFreitas;EdsonCavalcantiNeto; 15. Evaluation of Block-Matching 3D and Wavelet Transform with ShrinkThresholding Technique for Digital Mammography Denoising - Helder Oliveira, USP; Polyana Nunes, USP; Lucas Borges, USP; Predrag Bakic, UPENN;AndrewMaidment,UPENN;MarceloVieira,USP; 16. AnalysisoftheWisconsinBreastCancerDatasetandMachineLearningfor BreastCancerDetection-LucasBorges,USP; 17. Analysis of the Influence of Distance Metrics on the Semi-supervised Algorithm of Particle Competition and Cooperation - Lucas Guerreiro, UNESP;FabrícioBreve,UNESP 18. Preprocessing Images to Improve Deep Neural Networks Classification - Horst Erdmann, Boolabs; Fernando Ito, UFSCar; Danilo Santos, Boolabs; DanielTakabayashi,Boolabs;JanderMoreira,UFSCar; 19. Parallelization of the Particle Competition and Cooperation Approach for Semi-SupervisedLearning-RaulSouza,UNESP;FabrícioBreve,UNESP; 20. System for Corneal Ulcer Analysis - Luciana Almansa, DCM/USP; Sidney Sousa,FFCLRP/USP;Jean-JacquesDeGroote,Estácio; 21. Information Portal to Support Research in Bone Age Estimation - André Silva; Celso Olivete, FCT/UNESP; Rogério Garcia, FCT/UNESP; Ronaldo MessiasCorreia,FCT/UNESP; THISPRESENTATIONWASMOVEDTOPOSTERSESSION2 25 XIWorkshopdeVisãoComputacional-October05th–07th,2015 22. Implementation and Research of Parallel Computing Algorithms for the CharacterizationofMedicalImages-MatheuSantos,UESC;PedroOliveira, UESC;MarceloHonda,UESC; 23. Automatic Translation of Brazilian Sign Language (LIBRAS) with Hidden MarkovModels(HMM):Usingsamplesofdeaf,interpretersandastudent ofLIBRAS-DiegoDias,UFSCar;EdnaldoPizollato,UFSCar; 24. Radial Search Algorithm: A Gesture Recognition Algorithm to Real-time Systems-VirgilioLima,UEFS;JoãoGertrudes,UEFS; 25. Supervised Traffic Signs Recognition in Digital Images using Interest Points- Matheus Gutoski, UDESC; Chidambaram Chidambaram, UDESC; GilmáriodosSantos,UDESC; 26. ApplicationofanApproachBasedonToleranceNearSetsinMangoColor Detection-DiegoSaqui,UFSCAR;JoséSaito,UFSCAR;LucioJorge,Embrapa; RodrigoPiassi; 27. FishSpeciesRecognitionusingTemplateMatchingandLocalDescriptors- Gercina Silva, INOVISAO/UCDB; Ueliton Freitas, UFMS; Rafael Telles, UCDB; HemersonPistori,UCDB; 26 28. An Automatic Methodology for Face Shape Identification on Images - MagjeanderSilva,UFMG;EricksonNascimento,UFMG; XIWorkshopdeVisãoComputacional-October05th–07th,2015 27 XIWorkshopdeVisãoComputacional-October05th–07th,2015 PosterSession2 th Tuesday-October06 -15:40hto17:30h Chair: ValdirGrassiJr. Co-Chairs: MaurílioBoaventura EvandroLuisLinhariRodrigues InêsA.G.Boaventura LuizA.P.Neves MauricioMarengoni 28 1. Content-BasedImageRetrievalinMedicalImagestosupportaComputerAided Diagnosis - Ronaldo Costa, UFG; Elias Macena, INF/UFG; Rogerio Salvini,INF/UFG;LeandroOliveira,INF/UFG;FátimaNunes,EACH/USP; 2. Automatic Identification of Trees from Aerial Images of the Internet to Prevent Failures in Power Distribution System - Ronaldo Costa, UFG; Heuber Lima, INF/UFG; Anderson Soares, INF/UFG; Gustavo Laureano, INF/UFG; 3. Automatic Correction of Multiple-Choice Tests on Android Devices - FranciscoZampirolli,UFABC;RodrigoChina,UFABC;RogérioNeves,UFABC; JoséGuilici-Gonzalez,UFABC; 4. Recognition of Vehicles Logos using SURF - Cristiano Macedo, UFSCAR; MarcioFernandes; 5. Aq-GaussianSpatialFiltering-CelsoGallão,FEI;PauloSilvaRodrigues,FEI; 6. IdentificationofFoliarSoybeanDiseasesusingLocalDescriptors-Jonatan Patrick Oruê, UFMS; Wesley Gonçalves, UFMS/CPPP; Wesley Eiji Kanashiro, UFMS/FACOM; Rillian Diello Pires, UFMS/FACOM; Bruno Machado, UFMS/CPPP;MauroArruda,UFMS/CPPP; 7. RecognitionofSoybeanInsectPestsusingSURFandTemplateMatching- Diogo Soares, FACOM - UFMS; Gercina Silva, INOVISAO/UCDB; Ariadne Gonçalves,INOVISAO/UCDB;LucasTorres,UCDB;HemersonPistori,UCDB; 8. Comparison of Feature Spaces in Fruit Recognition - Marcela Nishida, UNESP;DaniloEler,UNESP;AlmirArtero,UNESP;MaurícioDias,UNESP; 9. Comparison of Computer Techniques for Handwritten Character Recognition - Priscila Macanhã, UNESP; Danilo Eler, UNESP; Almir Artero, UNESP; XIWorkshopdeVisãoComputacional-October05th–07th,2015 10. Classification of Diaphorina citri into Microscopy Images - José Leonardo Melo, UEFS; Michele F. Angelo, DTEC-UEFS; Marcelo Miranda, FUNDECITRUS; 11. ALowCostEmbeddedSystemwithComputerVisionandVideoStreaming- AndréCurvello,USP;EvandroRodrigues,USP;ThiagoLima; 12. PDIExp: Web Platform for Direct Experimentation of Computer Vision Methods-LenonFachiano;CelsoOlivete;PedroReis,UNESP;RafaelSantos; RonaldoMessiasCorreia,FCT/UNESP;RogérioGarcia,FCT/UNESP; 13. AverageGrainSizeEstimationonMetallicMaterialsusingImageAnalysis- Diego Araujo, Federal University of Ouro Preto; Geraldo Faria, Federal UniversityofOuroPreto;GladstonMoreira,UFOP;DavidMenotti,UFOP; 14. Automatic Counting and Measuring Fish Oocytes from Microscopic Images- Jonathan Ramos, USP; Carolina Watanabe, UNIR; Agma Traina, ICMC/USP;DiogoHungria,UNIR;TallesColaço,UNIR;CarolinaDória,UNIR; 15. InvestigatingColorModelsforCellularSegmentationofWhiteBloodCells- Thaína Tosta, UFU; Andrêssa de Abreu, UFU; Diogo Vilela, USP; Leandro Neves, USP; Bruno Travençolo, FACOM/UFU; Marcelo Zanchetta, FACOM/UFU; 16. Auto Feature Weight for Interactive Image Segmentation using Particle CompetitionandCooperation-FabrícioBreve,UNESP; 17. Thermal Image Segmentation in Studies of Wildlife Animals - Mauro de Arruda,UFMS;BrunoMachado,UFMS;WesleyGonçalves,UFMS/CPPP;João HenriqueDias,CESP;LauryCullen,CESP;CristinaGarcia,CESP;JoseJr,USP; 18. Method Based in Corner and Edge Detection to Separate Soybean SeedlingsStructures-DanielLima,USP;EvandroRodrigues,EESC/USP;Lucio Jorge,Embrapa; 19. Comparative Study on Otsu, EICAMM and Level Set Techniques to Automatic Segmentation of Breast Lesions in Digital Mammography - KaremMarcomi,USP;HomeroSchiabel,USP; 20. Ship Segmentation in Sluice - Fagner Pimentel, UFBA; Michele Angelo, DTEC/UEFS;DiegoFrias,UNEB; 21. Illumination-invariant Image Segmentation for Robot Soccer - Sávio Cantero,UFMS;WesleyGonçalves,UFMS/CPPP; 22. Application of Gaussian Markov Random Fields in Citrus Segmentation - JoãoHerrera,Embrapa;LeandroCandido,Embrapa;LucioJorge,Embrapa; 29 XIWorkshopdeVisãoComputacional-October05th–07th,2015 23. IndoorSimulationforControlofUnmannedAerialVehicles-RicardoVergili Filho,UFABC;OswaldoFratiniFilho;FranciscoZampirolli,UFABC; 24. Visão Computacional Aplicada a Dispositivos Móveis para Automação Robótica-GuilhermeG.Moreira,SENAC;MarioL.P.Toledo,SENAC;FábioR. deMiranda,SENAC; 25. The Use of Computing Vision and Affective Computing in Building Humanoid Robots - Luiz Pereira Neves, UFPR; Reginaldo Silveira, UniBrasil; Maria Costa, UFPR; Andreia Jesus, UFPR; Rafaela Otemaier, UFPR; José Feger,UFPR; 26. A Visual Attention Approach for the Tracking of Vehicles Through UAV - Raphael Montanari, USP; Daniel Tozadore, USP; Eduardo Fraccaroli, USP; AlcidesBenicasa,UFS;RoseliRomero,USP; 27. Traffic Sign Detection and Recognition using the AdaBoost and Transition Between Pixels - Francisco Silva, UNOESTE; João Paulo Masiero, UNOESTE; DanilloPereira,UNOESTE;AlmirArtero,UNESP;MarcoPiteri,UNESP; 28. Vehicles Classification Using Optical Flow - Fernando Castro, UNOESTE; Francisco Silva, UNOESTE; Danillo Pereira, UNOESTE; Almir Artero, UNESP; MarcoPiteri,UNESP; 29. Identification and Tracking of People Using Digital Images Captured from VideoCameras-LucasManuel,UNOESTE;FranciscoSilva,UNOESTE;Danillo Pereira,UNOESTE;AlmirArtero,UNESP;MarcoPiteri,UNESP; 30. Information Portal to Support Research in Bone Age Estimation - André Silva; Celso Olivete, FCT/UNESP; Rogério Garcia, FCT/UNESP; Ronaldo MessiasCorreia,FCT/UNESP; 30 XIWorkshopdeVisãoComputacional-October05th–07th,2015 31 XIWorkshopdeVisãoComputacional-October05th–07th,2015 UsefulPhoneNumbers SEL/EESC/USP (16)3373-9371 CampusSecurityStaff (16)3373-9112 PoliceDept. 190 MedicalEmergency(SAMU) 192 FireDept.andRescue 193 MedicalEmergency(SantaCasa) (16)3509-1100 Taxi (16)3415-6005 32 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 33 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 34 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 35 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 36 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 37 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 38 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 39 XIWorkshopdeVisãoComputacional-October05th–07th,2015 Annotations 40