A 201.4 GOPS 496 mW Real-Time Multi-Object Recognition Proce(13)

A 201.4 GOPS real-time multi-object recognitionprocessor is presented with a three-stage pipelined architecture.Visual perception based multi-object recognition algorithm isapplied to give multiple attentions to multiple objects in the inputimage. For human-like multi-object perception, a neural perceptionengine is proposed with biologically inspired neural networksand fuzzy logic circ

44circuits.Inhardwarearchitecture,athree-stagepipelinedar-chitecturehasbeenproposedtomaximizethethroughputofrecognitionprocessing.Thethreeobjectrecognitiontasksareexecutedinthepipelineandtheexecutiontimesofthethreetasksarebalancedforef cientpipeliningbasedonintelligentworkloadestimations.Inaddition,a118.4GB/smulti-castingnetwork-on-chiphasbeenproposedforcommunicationarchi-tecturewithincorporatingoverall21IPblocksoftheprocessor.Finally,workload-awaredynamicpowermanagementwasperformedforlow-powerobjectrecognition.The49mmchipcontains3.7Mgatesand396KBon-chipSRAMina

0.13mCMOSprocess.Withademonstrationsystem,thefabricatedchipachieves60frame/secmulti-objectrecognition

upto10differentobjectsforVGA

(640

480)videoinputwhiledissipating496mWat1.2V.Theobtained8.2mJ/frameenergydissipationis3.2timeslowerthanthestate-of-the-artrecognitionprocessor.

REFERENCES

[1]S.Kyoetal.,“A51.2GOPSscalablevideorecognitionprocessorfor

intelligentcruisecontrolbasedonalineararrayof1284-wayVLIWprocessingelements,”IEEEJ.Solid-StateCircuits,vol.38,no.11,pp.1992–2000,Nov.2003.

[2]A.Abboetal.,“XETAL-II:A107GOPS,600mWmassively-parallel

processorforvideosceneanalysis,”IEEEJ.Solid-StateCircuits,vol.43,no.1,pp.192–201,Jan.2008.

[3]D.Kimetal.,“An81.6GOPSobjectrecognitionprocessorbasedon

NoCandvisualimageprocessingmemory,”inProc.IEEECustomIn-tegratedCircuitsConf.(CICC),Apr.2007,pp.443–446.

[4]K.Kimetal.,“A125GOPS583mWnetwork-on-chipbasedparallel

processorwithbio-inspiredvisualattentionengine,”IEEEJ.Solid-StateCircuits,vol.44,no.1,pp.136–147,Jan.2009.

[5]J.-Y.Kimetal.,“A201.4GOPS496mWreal-timemulti-objectrecog-nitionprocessorwithbio-inspiredneuralperceptionengine,”inIEEEISSCCDig.Tech.Papers,Feb.2009,pp.150–151.

[6]D.G.Lowe,“Distinctiveimagefeaturesfromscale-invariantkey-points,”http://www.77cn.com.cnputerVision,vol.60,no.2,pp.91–110,Jan.2004.

[7]S.Leeetal.,“Thebrainmimickingvisualattentionengine:An802

60digitalcellularneuralnetworkforrapidglobalfeatureextraction,”inIEEESymp.VLSICircuitsDig.,Jun.2008,pp.26–27.

[8]L.Ittietal.,“Amodelofsaliency-basedvisualattentionforrapidscene

analysis,”IEEETrans.PatternAnal.MachineIntell.,vol.20,no.11,pp.1254–1259,Nov.1998.

[9]M.Kimetal.,“A22.8GOPS2.83mWneuro-fuzzyobjectdetection

engineforfastmulti-objectrecognition,”inIEEESymp.VLSICircuitsDig.,Jun.2009,pp.260–261.

[10]S.A.Nene,S.K.Nayar,andH.Murase,ColumbiaObjectImageLi-brary(Coil-100),ColumbiaUniversity,NewYork,TechnicalReportCUCS-006-96,Feb.1996.

[11]S.Agarwaletal.,“Learningtodetectobjectsinimagesviaasparse,

part-basedrepresentation,”IEEETrans.PatternAnal.MachineIntell.,vol.26,no.11,pp.1475–1490,Nov.2004.

[12]J.-Y.Kimetal.,“A66frame/sec38mWnearestneighbormatching

processorwithhierarchicalVQalgorithmforreal-timeobjectrecogni-tion,”inProc.IEEEA-SSCC,Nov.2008,pp.177–180.

[13]P.Pirsch,N.Demassieux,andW.Gehrke,“VLSIarchitectures

forvideocompression—Asurvey,”Proc.IEEE,vol.83,no.2,pp.220–246,Feb.1995.

[14]D.O.Hebb,TheOrganizationofBehavior.NewYork:Wiley,1949.[15]S.-J.Leeetal.,“An800MHzstar-connectedon-chipnetworkforap-plicationtosystemsonachip,”inIEEEISSCCDig.Tech.Papers,2003,pp.468–489.

[16]K.Leeetal.,“Low-powernetworks-on-chipforhigh-performanceSoC

design,”IEEETrans.VLSISyst.,vol.14,no.2,pp.148–160,Feb.2006.[17]K.Kimetal.,“A76.8GB/s46mWlow-latencynetwork-on-chipfor

real-timeobjectrecognitionprocessor,”inProc.IEEEA-SSCC,Nov.2009,pp.177–180.

[18]J.N.Seizovic,“Pipelinesynchronization,”inProc.IEEEASYNC,Nov.

1994,pp.87–96.

IEEEJOURNALOFSOLID-STATECIRCUITS,VOL.45,NO.1,JANUARY2010

[19]M.Keatingetal.,LowPowerMethodologyManualforSystemonChip

Design.NewYork:Springer,2007.

[20]B.Khailanyetal.,“Aprogrammable512GOPSstreamprocessorfor

signal,image,andvideoprocessing,”inIEEEISSCCDig.Tech.Pa-pers,Feb.2007,pp.

272–273.

Joo-YoungKim(S’05)receivedtheB.S.andM.S.degreesinelectricalengineeringandcomputersci-encefromtheKoreaAdvancedInstituteofScienceandTechnology(KAIST),Daejeon,Korea,in2005and2007,respectively,andiscurrentlyworkingto-wardthePh.D.degreeinelectricalengineeringandcomputerscienceatKAIST.

Since2006,hehasbeeninvolvedwiththedevelop-mentoftheparallelprocessorsforcomputervision.Currently,hisresearchinterestsareparallelarchitec-ture,sub-systems,andVLSIimplementationforbio-inspiredvision

processor.

MinsuKim(S’07)receivedtheB.S.andM.S.de-greesinelectricalengineeringandcomputersciencefromtheKoreaAdvancedInstituteofScienceandTechnology(KAIST),Daejeon,Korea,in2007and2009,respectively.HeiscurrentlyworkingtowardthePh.D.degreeinelectricalengineeringandcom-puterscienceatKAIST.

Hisresearchinterestsincludenetwork-on-chipbasedSoCdesignandbio-inspiredVLSIarchitectureforintelligentvision

processing.

SeungjinLee(S’06)receivedtheB.S.andM.S.de-greesinelectricalengineeringandcomputersciencefromtheKoreaAdvancedInstituteofScienceandTechnology(KAIST),Daejeon,Korea,in2006and2008,respectively.HeiscurrentlyworkingtowardthePh.D.degreeinelectricalengineeringandcom-putersciencefromKAIST.

Hispreviousresearchinterestsincludelow-powerdigitalsignalprocessorsfordigitalhearingaidsandbodyareacommunication.Currently,heisinvesti-gatingparallelarchitecturesforcomputervisionpro-

cessing.

JinwookOh(S’08)receivedtheB.Sdegreeinelec-tricalengineeringandcomputersciencefromSeoulNationalUniversity,Seoul,Korea,in2008.Heiscur-rentlyworkingtowardtheM.S.degreeinelectricalengineeringandcomputerscienceatKAIST,Dae-jeon,Korea.

Hisresearchinterestsincludelow-powerdigitalsignalprocessorsforcomputervision.Recently,heisinvolvedwiththeVLSIimplementationofneuralnetworksandfuzzy

logics.

KwanhoKim(S’04)receivedtheB.S.andM.SdegreesinelectricalengineeringandcomputersciencefromtheKoreaAdvancedInstituteofSci-enceandTechnology(KAIST)in2004and2006,respectively.HeiscurrentlyworkingtowardthePh.D.degreeinelectricalengineeringandcomputerscienceatKAIST.

In2004,hejoinedtheSemiconductorSystemLaboratory(SSL)atKAISTasaResearchAssistant.HisresearchinterestsincludeVLSIdesignforobjectrecognition,architectureandimplementationof

NoC-basedSoC.

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