基于计算机视觉的电梯轿厢智能监控系统的研究与设计

基于计算机视觉的电梯轿厢智能监控系统的研究与设计基于计算机视觉的电梯轿厢智能监控系统的研究与设计

摘要

为了保障人们的生命财产安全，电梯轿厢监控系统逐渐变成一个重要的场所监控领域。本文提出了一种基于计算机视觉的电梯轿厢智能监控系统，该系统可以实现电梯轿厢内的目标检测、跟踪、异常行为检测和人脸识别等功能，有效地提高了电梯轿厢的安全性和管理水平。

本文首先介绍了电梯轿厢监控系统的研究背景和现状。然后，针对目标检测和跟踪问题，提出了基于深度学习的目标检测器YOLOv3和基于卡尔曼滤波的目标跟踪算法。针对异常行为检测问题，提出了基于深度学习的行为识别模型和基于分类器的异常行为检测方法。针对人脸识别问题，提出了基于深度学习的人脸检测和识别模型。

最后，本文设计和实现了一个基于计算机视觉的电梯轿厢智能监控系统原型。该系统采用了基于深度学习的目标检测器YOLOv3、基于卡尔曼滤波的目标跟踪算法、基于行为识别模型的异常行为检测和基于深度学习的人脸检测和识别模型等技术。实验结果表明：本系统可以有效地实现电梯轿厢内人员目标检测、跟踪、异常行为检测和人脸识别等功能，具有较高的实用性和可靠性。

关键词：电梯轿厢，计算机视觉，目标检测，目标跟踪，异常行为检测，人脸识别

Abstract

Inordertoensurethesafetyofpeople'slivesandproperty,theelevatorcarmonitoringsystemhasgraduallybecomeanimportantplacemonitoringfield.Thispaperproposesacomputervision-basedintelligentmonitoringsystemforelevatorcars,whichcanrealizefunctionssuchastargetdetection,tracking,abnormalbehaviordetectionandfacerecognitionintheelevatorcar,effectivelyimprovingthesafetyandmanagementleveloftheelevatorcar.

Thispaperfirstintroducestheresearchbackgroundandstatusoftheelevatorcarmonitoringsystem.Then,forthetargetdetectionandtrackingproblems,adeeplearning-basedtargetdetectorYOLOv3andaKalmanfilter-basedtargettrackingalgorithmareproposed.Fortheabnormalbehaviordetectionproblem,abehaviorrecognitionmodelbasedondeeplearningandaclassifier-basedabnormalbehaviordetectionmethodareproposed.Forthefacerecognitionproblem,adeeplearning-basedfacedetectionandrecognitionmodelisproposed.

Finally,thispaperdesignsandimplementsaprototypeofacomputervision-basedintelligentmonitoringsystemforelevatorcars.Thesystemadoptstechnologiessuchasadeeplearning-basedtargetdetectorYOLOv3,aKalmanfilter-basedtargettrackingalgorithm,anabnormalbehaviordetectionbasedonbehaviorrecognitionmodel,andadeeplearning-basedfacedetectionandrecognitionmodel.Experimentalresultsshowthatthesystemcaneffectivelyachievefunctionssuchastargetdetection,tracking,abnormalbehaviordetectionandfacerecognitionofpersonnelintheelevatorcar,andhashighpracticalityandreliability.

Keywords:elevatorcar,computervision,targetdetection,targettracking,abnormalbehaviordetection,facerecognitioTheproposedcomputervisionsystemforelevatorcarsiscomposedofmultiplemodulesincludingtargetdetection,targettracking,abnormalbehaviordetection,andfacerecognition.Thesystemutilizesalightweightandefficienttargetdetectionalgorithm,whichcanquicklydetectandlocatetheelevatorpassengers.Thetargettrackingmoduleusesadvancedalgorithmstotrackthemovementofindividualsintheelevatorcar,evenincomplexsituationswithocclusionsandoverlap.

Todetectabnormalbehaviorofpassengers,thebehaviorrecognitionmodelisintroduced.Thismodelrecognizesasetofpredefinedbehaviors,includingaggressivebehavior,suspiciousbehavior,andwanderingbehavior,andtriggersanalarmwhensuchbehaviorsaredetected.Thisgreatlyenhancesthesecurityoftheelevatorcarandhelpstopreventpotentialsafetyhazards.

Thefacedetectionandrecognitionmoduleofthesystemadoptsdeeplearning-basedalgorithms,whicharehighlyaccurateandefficientforidentifyingindividualsinreal-time.Bycomparingthecapturedimagewiththedatabaseofrecordedfaces,thesystemcanaccuratelyidentifyindividualsandprovidenecessaryaccesscontrol.

Experimentalresultsshowthattheproposedcomputervisionsystemhashighaccuracyintargetdetection,tracking,abnormalbehaviorrecognition,andfacerecognitionofpersonnelintheelevatorcar.Thesystemisalsohighlypractical,andhasstrongreliabilityinreal-worldscenarios.

Inconclusion,theproposedcomputervisionsystemoffersgreatpotentialforimprovingsafetyandsecurityinelevatorcars.Thesystemcanalertthesecuritypersonnelinreal-timeandhelppreventdangeroussituations.Thistechnologyopensupnewpossibilitiesforsmartelevatorsystems,whichcanfurtherenhancepassengersafetyandcomfortOnepotentialapplicationofthistechnologyisinhigh-risebuildingswhereelevatorsareacriticalmeansoftransportforpeopleandgoods.Oftensuchbuildingshaverestrictedaccessandstrictsecurityprotocolstopreventunauthorizedentry.Theproposedsystemcanhelpthesecuritypersonneltoautomaticallyidentifypeoplewhoareauthorizedtoaccessthebuildingandflaganysuspiciousactivity.Thiscanhelppreventunauthorizedaccessandpreventsecuritybreaches.

Anotherpotentialbenefitofthistechnologyisinimprovingthecomfortandconvenienceofpassengers.Thesystemcanautomaticallyrecognizefrequentlyusedfloorsandpre-selectthemforthepassengers.Thiscansignificantlyreducewaitingtimesandimprovetheoverallefficiencyoftheelevatorsystem.Additionally,thesystemcanalsotrackelevatorusagepatternsandoptimizetheelevatorservicebasedontheusagedata.Forexample,ifthesystemnoticesthataparticularelevatorishighlyusedduringpeakhours,itcanreroutetheelevatortothefloorwiththehighestdemand.

Overall,theproposedcomputervisionsystemhasthepotentialtorevolutionizethewayweinteractwithelevators.Itcanimprovethesafety,security,andcomfortofpassengerswhilealsoofferingsignificantbenefitstobuildingownersandoperators.Withcontinuedresearchanddevelopment,thistechnologycanhelppavethewayforsmartelevatorsystemsthatarehighlyefficient,safe,andreliableOnepotentialapplicationforcomputervisioninelevatorsisintheareaofpredictivemaintenance.Byconstantlymonitoringtheelevator'scomponentsandsystems,thecomputervisionsystemcandetectanypotentialissuesormalfunctionsbeforetheybecomeseriousproblems.Thiscanhelppreventunexpectedbreakdownsandreducedowntime,whichisespeciallyimportantinhigh-trafficareassuchasofficebuildings,hospitals,andshoppingcenters.

Anotherpotentialbenefitofcomputervisioninelevatorsisintheareaofaccessibility.Elevatorscanbeequippedwithsensorsandcamerasthatdetectthepresenceofpassengersandadjusttheelevator'sbehavioraccordingly.Forexample,ifapassengerwithamobilityimpairmententerstheelevator,thecomputervisionsystemcandetecttheirpresenceandautomaticallyadjusttheelevator'sspeed,acceleration,andbrakingtoensureasmoothandcomfortableride.

Finally,computervisioncanalsobeusedtoimprovetheoveralluserexperienceofelevators.Forexample,thesystemcandetectpassengerpreferencesandadjustthelighting,temperature,andmusicaccordingly.Itcanalsoprovidereal-timeinformationaboutwaittimes,elevatorcapacity,andupcomingfloors,whichcanhelpreducepassengeranxietyandimproveoverallsatisfaction.

Inconclusion,computervisionhasthepotentialtorevolutionizethewayweinteractwithelevators.Fromimprovingsafetyandsecuritytoenhancin