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
KIMetal.:A201.4GOPS496mWREAL-TIMEMULTI-OBJECTRECOGNITIONPROCESSORWITHBIO-INSPIREDNEURALPERCEPTIONENGINE
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Fig.16.(a)GOPS/Wcomparison.(b)Energy/frame
comparison.
Fig.17.Demonstrationsystem.
TABLEICHIPS
UMMARY
TABLEII
POWERBREAK-D
OWN
processorachieves8.2mJenergydissipationperframeforVGAsizedvideoinput,whichis3.2timeslowerthanthebestofthepreviousobjectrecognitionprocessor.
Forthevalidationofthefabricatedchip,ademonstrationsystemforreal-timeobjectrecognitionisdevelopedasshowninFig.17.Itiscomposedoftargetobjects,videocamcorder,evaluationboard,andLCDdisplay.Theevaluationboardiscomposedofthree oors,whichareforhostprocessor,videodecoderandfabricatedrecognitionchip,andperipheralinterfacessuchasLCDdisplay,serial,USB,andEthernet,respectively.Inthedemonstrationsystem,thefabricatedchipisusedasavisionprocessingacceleratorwhilethehostprocessorcontrolsthewholeprogramsequencesandaccessesperipheralmodulestodisplaytheresultsandtointerfacewiththeexternaldevices.Theoverallobjectrecognitionisperformedbythreesteps.First,theinputimageofthetargetobjectsiscapturedfromthevideocamcorderanddecodedtothree-channelRGBpixeldatabythevideodecoder.Then,http://www.77cn.com.cnst,the nalrecognitionresultsaredisplayedwiththekey-pointsattheLCDscreenbythehostprocessor.
VIII.CONCLUSION
Inthiswork,wehaveproposedareal-timemulti-objectrecognitionprocessorwithathree-stagepipelinedarchitec-ture.Thevisualperceptionbasedmulti-objectrecognitionalgorithmhasbeendevelopedtogivemultipleattentionstomultipleobjectsintheinputimage.Forhuman-likemulti-ob-jectperception,aneuralperceptionenginehasbeenproposedwithbiologicallyinspiredneuralnetworksandfuzzylogic