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Transcript of Robust 3D Head Pose Classification using Wavelets by Mukesh C. Motwani Dr. Frederick C. Harris, Jr.,...
![Page 1: Robust 3D Head Pose Classification using Wavelets by Mukesh C. Motwani Dr. Frederick C. Harris, Jr., Thesis Advisor December 5 th, 2002 A thesis submitted.](https://reader035.fdocuments.net/reader035/viewer/2022062515/56649cf85503460f949c8f6e/html5/thumbnails/1.jpg)
Robust 3D Head Pose Robust 3D Head Pose Classification using Classification using WaveletsWavelets
byby
Mukesh C. MotwaniMukesh C. Motwani
Dr. Frederick C. Harris , Jr., Thesis AdvisorDr. Frederick C. Harris , Jr., Thesis Advisor
December 5December 5thth, 2002, 2002
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Engineering
University of Nevada, Reno
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OverviewOverview
Problem DescriptionProblem Description Proposed SolutionProposed Solution
Wavelets and PCA Wavelets and PCA Future WorkFuture Work Questions and AnswersQuestions and Answers DemoDemo
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What is Pose Classification What is Pose Classification ??
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Potential ApplicationsPotential Applications
Face RecognitionFace Recognition
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Potential ApplicationsPotential Applications
Virtual RealityVirtual Reality
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Potential ApplicationsPotential Applications
Video ConferencingVideo Conferencing
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Potential ApplicationsPotential Applications
RoboticsRobotics
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Potential ApplicationsPotential Applications
Driver VigilanceDriver Vigilance
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
IdentityIdentity
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
Face DetectionFace Detection
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
Facial ExpressionFacial Expression
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
Changes in distance from CameraChanges in distance from Camera
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
OcclusionOcclusion
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What makes Pose What makes Pose Detection so difficult?Detection so difficult?
Changes in IlluminationChanges in Illumination
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Previous WorkPrevious Work
Feature BasedFeature Based Appearance BasedAppearance Based Model BasedModel Based Other Combined ApproachesOther Combined Approaches
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Feature Based Pose Feature Based Pose DetectionDetection
Kalman FilterKalman Filter Gabor JetsGabor Jets Elastic Graph BunchingElastic Graph Bunching
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Appearance Based Pose Appearance Based Pose DetectionDetection
Template MatchingTemplate Matching Neural Networks / Wavelet Neural Neural Networks / Wavelet Neural
NetworksNetworks SVMSVM PCAPCA
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Model Based Pose Model Based Pose DetectionDetection
Skin ColorSkin Color AnthropometryAnthropometry
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Other Combined Other Combined ApproachesApproaches
Volumetric Frequency Volumetric Frequency RepresentationRepresentation
Hairline contourHairline contour Optical FlowOptical Flow
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PCA Based ApproachPCA Based Approach
““View Based”View Based” ““Parametric”Parametric”
1. Motivation for choosing PCA
2. Sub categories in PCA based approach
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Block DiagramBlock Diagram
Training StageTraining Stage
Training Images Training Images
Detection StageDetection Stage Detected Detected
PosePose
Query Query ImageImage
Discrete Wavelet Transform
Principal Component
Analysis
ManifoldPlot
Discrete Wavelet Transform
Principal Component
Analysis
Eigen SpaceProjection
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Wavelet TransformWavelet Transform
Filter BanksFilter Banks
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Wavelet TransformWavelet Transform
Subband DecompositionSubband Decomposition
Low Pass Output
High Pass Output
LL HL
LH HH
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DWT of Lena ImageDWT of Lena Image
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Selection of Resolution Selection of Resolution LevelLevelDistribution of energy in LL subband at different levels of discrete wavelet transform
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Selection of Resolution Selection of Resolution LevelLevel
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Principal component analysis Principal component analysis (PCA)(PCA)1. Mean Image (Enlarged)
2. Compute covariance matrix
3. Compute eigen-vectors and eigen-coefficients
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Manifold PlotManifold Plot
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ExperimentationExperimentation
Facial ExpressionFacial Expression
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ExperimentationExperimentation
Changes in distance from cameraChanges in distance from camera
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ExperimentationExperimentation
Changes in IlluminationChanges in Illumination
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ExperimentationExperimentation
Identity changeIdentity change
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PerformancePerformance
Classification accuracy of 84%Classification accuracy of 84% Real time capability 12-15 fpsReal time capability 12-15 fps
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ConclusionConclusion
FasterFaster More RobustMore Robust CheaperCheaper
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Future WorkFuture Work
Face DetectionFace Detection Identity IndependentIdentity Independent Undecimated Wavelet TransformUndecimated Wavelet Transform
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Questions ? / Answers Questions ? / Answers Real-time DemoReal-time Demo