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Summary of important papers for the lecture "Non-Rigid-Deformation" $22.12   Add to cart

Summary

Summary of important papers for the lecture "Non-Rigid-Deformation"

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Summary of the papers: 1. Global correspondence optimisation for non-rigid registration of Depth Scans 2. Real-time non-rigid-reconstruction using an Rgb-D-camera 3. ARAP

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  • August 15, 2022
  • 2
  • 2022/2023
  • Summary
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forpointclouds
bae correspondence optimisationfornonrigidregistration ofDepthscans slap
Glo

forpartialscansofdeformingshapesthataddressesthechallengesofnonrigidregistrationwithinasinglenon
algorithm
linear
optimization
registration

This
algorithm wasfor
simultaneouslyso thereliabilityofeach
correspondencesconfidenceweightsthat
measure c orrespondence

and
identifiesnonoverlappingareasandawarping that
field thesourcescanintoalignmentwith
brings thetargetgeometry
local
poor minimaare avoidedwithaniterativeexecutionscheme thatdetectssuboptimaeconvergenceand the
restarts
theoptimizationwithimprovedinitialconditionssothatbetterresultisobtained
employsanon
Thealgorithm systemthat
lineardeformation favorsnaturaldeformationsbymaximizingboth
rigidity
andconsistency
Theoptimizationoswessimultaneouslyforboththedeformationparametersaswellasthecorrespondentpositions
sincesome sourcepointshave nocorrespondingpositiononthetargetduetopartialoverlapweaugment
eachcorrespondencewithaweightthatisalsosowedforbythe optimizer


Deformationmodel


sourcescanisaugmentedwitharedureddeformablemodelintheformof a graph deformation

Esmoon serves as aregularizesforthedeformationbyindicatingthatthe
affinetransformations
ofadjacentgraphnodesshouldagreewithoneanother
erigid penalizesthedeviationofeachtransformationfromapurerigidmotion
consequentlylocalfeatures
deformasrigidly aspossible shearingorstretchingartifacts
avoiding
strivestomoveeachsourcegraphnodetoits correspondingpositiononthe
targetshape
exit
Esont aimsatmaximizingthenumber
maximizestheregion
ofreliablecorrespondencesbypushingtheweightstowardsonethus
ofoverlap



RealtimenonrigidreconstructionusinganRab Dcamera cmapsoobjecttopointcloud

I create a JD model
2 nonrigid registrationofliveratsDdatatothe smoothtemplate
usinganextendednonlinearasrigidas possibleCARAP framework

realtimenonrigidreconstruction

rigidregistration roughlyalignsthetemplatetotheinputdata
2 Nonrigidsurfacefitting
minimization
offittingenergywhichcombinesdensegeometricandphotometricmodeltodata
constraints APregularizer
aswellasanasrigidaspossiblecar
Gauss usingthe
solver
Newton preconditionedconjugate method
gradient spca inits
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innerloop
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acquisition
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ateachlevelthe energyis
fitting optimized atthe
currentresolution iterations GaussNewton
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