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cvpr2013-Modeling Mutual Visibility Relationship in Pedestri(7)

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发表在CVPR13上的行人检测方法

Figure7.ExperimentalresultsontheCaltech-Testdataset(left)andthePETS2009dataset(right).

groundtruthpedestrianisconsideredasoverlappediftheoverlappingarearatioofhis/herboundingboxwithotherpedestrianislargerthan1%.PedestriansoverlappingwithotherpedestriansarecalledO-pedestriansinthispaper.TheO-pedestriansareinsubsetOverlapped.IsolatedPedestri-ansareinsubsetIsolatedandcalledI-pedestrians.Ourap-proachfocusesonO-pedestrians.NotethatanO-pedestrianisstillapedestrian.Fig.9showsexamplesonI-pedestrianandO-pedestrian.

Inthissection,wespeci callyevaluatethedetectionper-formanceondetectingI-pedestriansandO-pedestrians.Fig.10showstheexperimentalresults.TheimprovementofourapproachoverD-Isolis2%ondetectingI-pedestriansforbothdatasets.Ontheotherhand,theimprovementonde-tectingO-pedestriansis5%fortheCaltech-Traindatasetand7%fortheETHdataset.Thusourapproachout-performsD-Isolonpedestriandetectionmainlybecauseofitsabilityindetectingco-existingpedestrians,i.e.O-pedestrians.Thisexperimentalresultvalidatesthefocusofthispaperinimprovingtheperformanceondetectingpedes-trianswithoverlaps.

An I-pedestrian3 O-pedestrians

Figure9.I-pedestrianversus

O-pedestrian.

Figure10.ExperimentalresultsondetectingIsolatedpedestrians(top)andOverlappedpedestrians(bottom)ontheCaltech-Traindataset(left)andtheETHdataset(right).

6.Conclusion

Thispaperproposesamutualvisibilitydeepmodelthatjointlyestimatesthevisibilitystatusesofmultipleco-existingpedestrians.Startingfromthescoresofconven-tionalpartdetectors,http://www.77cn.com.cnparedwithexistingimage-basedpedestriandetectionapproacheseval-uatedin[9],ourapproachachievesthelowestmissrateontheCaltech-Traindataset,theCaltech-TestdatasetandtheETHdataset.Sincethedeepmodeltakesthepartdetectionscoresasinput,itiscomplementarytonewinvestigationsonfeatures,e.g.colorselfsimilarity,localbinarypattern,motionanddepth,andarticulationmodels,e.g.poselets,multi-objectarticulationmodel.Experimentalresultsonfourpubliclyavailabledatasetsshowthatthemutualvisi-bilitydeepmodeliseffectiveinimprovingpedestriande-tectionresults.

Acknowledgment:ThisworkissupportedbytheGen-eralResearchFundsponsoredbytheResearchGrantsCouncilofHongKong(ProjectNo.CUHK417110andCUHK417011),NationalNaturalScienceFoundationof

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