robust principal axes determination for point-based shapes
DESCRIPTION
Project Activity - January 2013 Software Engineering Module Burgundy University VIBOT Promotion 7 (2012-2014) Reference: Liu, Y.-S. & Ramani, K. (2009), 'Robust principal axes determination for point-based shapes using least median of squares.', Computer-Aided Design 41 (4) , 293-305 .TRANSCRIPT
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Group MembersIbrahim Sadek
Mohamed Elawady
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Robust principal axes determination for point-based
shapes
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Overview
Framework
Discussion & Results
Conclusion & Future Work
Agenda
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Overview
Use (Least Median of Squares)
instead of (Least Mean of Squares)3
Major & Minor Regions
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Framework
Calculate principal component axes based on LMS & forward search technique
Extract the initial subset for forward search technique using octree-based approximation
Apply the proposed algorithm to some shape matching techniques with/without the effect of noise
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Framework
LMS RPA
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Discussion & Results
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Discussion & Results
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Run #1 Run #2 Run #3
Comparison of major regionsCommon (Chest, Abdomen)
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Discussion & Results
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Dog Human Horse
Comparison of major regionsCylinder-like Shape
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Discussion & Results
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Comparison of major regionsWith/Without Noise
Run #1Normal
Run #2Cropping
Run #3Gaussian Noise
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Discussion & Results
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Comparison of major regionsWith/Without Noise
Run #1 Run #2 Run #3
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Discussion & Results
3D Mesh Operations
PCA Computation
Octree Operations
3D Shape Matching
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Problems
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Conclusion
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Shape Noise PCABad
(Shape Matching)
Shape Noise RPCAGood
(Shape Matching)
All points PAs
Major points PAs
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Future Work
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• IN PROGRESS (Not Sure About Results!!)Fixing E2 & E3
• Needs Training !!
• Depends on dataset shapes
Choosing Correct
Parameters
• Iterative Cloud Points
• Transformation Matrix (depends on O & E1)
Shape Matching
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Questions?!15