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1、ExemplarsforObjectDetectionNoahSnavelyCS7670:September5,2011Announcements•Officehours:Thursdays1pm–2:30pm•CoursescheduleisnowonlineObjectdetection:wherearewe?Credit:Flickruserneilalderney123•Incredibleprogressinthelasttenyears•Betterfeatures,bettermode
2、ls,betterlearningmethods,betterdatasets•CombinationofscienceandhacksThe800-lbGorillaofVisionContests•PASCALVOCChallenge•20categories•Annualclassification,detection,segmentation,…challengesObjectdetectionperformance(2010)Objectdetectionperformance(2010)
3、The2011serveropenedforsubmissionstoday!Machinelearningforobjectdetection•Whatfeaturesdoweuse?–intensity,color,gradientinformation,…•Whichmachinelearningmethods?–generativevs.discriminative–k-nearestneighbors,boosting,SVMs,…•Whathacksdoweneedtogetthings
4、working?HistogramofOrientedGradients(HoG)HoGify10x10cells20x20cells[DalalandTriggs,CVPR2005]HistogramofOrientedGradients(HoG)HistogramofOrientedGradients(HoG)•LikeSIFT(ScaleInvariantFeatureTransform),but…–Sampledonadense,regulargrid–Gradientsarecontras
5、tnormalizedinoverlappingblocksHoGify10x10cells[DalalandTriggs,CVPR2005]20x20cellsHistogramofOrientedGradients(HoG)•Firstusedforapplicationofpersondetection[DalalandTriggs,CVPR2005]•CitedsinceinthousandsofcomputervisionpapersLinearclassifiers•Findlinear
6、functiontoseparatepositiveandnegativeexamplesxpositive:xwb0iixnegative:xwb0iiWhichlineisbest?[slidecredit:KristinGrauman]SupportVectorMachines(SVMs)•Discriminativeclassifierbasedonoptimalseparatingline(for2Dcase)•Maximizethemarginbetweenthepositi
7、veandnegativetrainingexamples[slidecredit:KristinGrauman]Supportvectormachines•Wantlinethatmaximizesthemargin.xpositive(y1):xwb1iiixnegative(y1):xwb1iiiForsupport,vectors,xwb1iSupportvectorsMarginC.Burges,ATutorialonSupportVectorMachinesf
8、orPatternRecognition,DataMiningandKnowledgeDiscovery,1998[slidecredit:KristinGrauman]Persondetection,ca.20051.Representeachexamplewithasingle,fixedHoGtemplate2.Learnasingle[linear]SVMasadetectorCodeavailable:http://pascal.inrialpes.fr/s