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1、ExemplarsforObjectDetectionNoahSnavelyCS7670:September5,2011Announcements?Officehours:Thursdays1pm–2:30pm?CoursescheduleisnowonlineObjectdetection:wherearewe?Credit:Flickruserneilalderney123?Incredibleprogressinthelasttenyears?Betterfeatures,bettermodels,betterlearningmethods,betterda
2、tasets?CombinationofscienceandhacksThe800-lbGorillaofVisionContests?PASCALVOCChallenge?20categories?Annualclassification,detection,segmentation,…challengesObjectdetectionperformance(2010)Objectdetectionperformance(2010)The2011serveropenedforsubmissionstoday!Machinelearningforobjectdet
3、ection?Whatfeaturesdoweuse?–intensity,color,gradientinformation,…?Whichmachinelearningmethods?–generativevs.discriminative–k-nearestneighbors,boosting,SVMs,…?Whathacksdoweneedtogetthingsworking?HistogramofOrientedGradients(HoG)HoGify10x10cells20x20cells[DalalandTriggs,CVPR2005]Histogr
4、amofOrientedGradients(HoG)HistogramofOrientedGradients(HoG)?LikeSIFT(ScaleInvariantFeatureTransform),but…–Sampledonadense,regulargrid–GradientsarecontrastnormalizedinoverlappingblocksHoGify10x10cells[DalalandTriggs,CVPR2005]20x20cellsHistogramofOrientedGradients(HoG)?Firstusedforappli
5、cationofpersondetection[DalalandTriggs,CVPR2005]?CitedsinceinthousandsofcomputervisionpapersLinearclassifiers?Findlinearfunctiontoseparatepositiveandnegativeexamplesxpositive:x?w?b?0iixnegative:x?w?b?0iiWhichlineisbest?[slidecredit:KristinGrauman]SupportVectorMachines(SVMs)?Discrimina
6、tiveclassifierbasedonoptimalseparatingline(for2Dcase)?Maximizethemarginbetweenthepositiveandnegativetrainingexamples[slidecredit:KristinGrauman]Supportvectormachines?Wantlinethatmaximizesthemargin.xpositive(y?1):x?w?b?1iiixnegative(y??1):x?w?b??1iiiForsupport,vectors,x?w?b??1iSupportv
7、ectorsMarginC.Burges,ATutorialonSupportVectorMachinesforPatternRecognition,DataMiningandKnowledgeDiscovery,1998[slidecredit:KristinGrauman]Persondetection,ca.20051.Representeachexamplewithasingle,fixedHoGtemplate2.Learnasingle[linear]SVMasadetectorCodeavailable:http://pascal.inrialpes
8、.fr/s
