Symmetry

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# Symmetry - PowerPoint PPT Presentation

Symmetry. Find points with shape edges using different threshold angles. Clustering based on points. Find matching clusters. Computer symmetry plane. My method. Previous pose normalization. Problems. A better way to do cluster ? How to evaluate matching clusters more properly

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## Symmetry

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Presentation Transcript
Symmetry
• Find points with shape edges using different threshold angles
Computer symmetry plane

My method

Previous pose normalization

Problems
• A better way to do cluster?
• How to evaluate matching clusters more properly
• Now using Gaussian mixture distribution
• The covariance matrices are restricted to be diagonal
• The distance score
Next
• Use other feature points ( find the points by learning )
• Use features along with (x,y,z) to do clustering
• Find 10 hard/easy ones in Cleft dataset
• Prepare points (Giving examples)
• Schedule a meeting with Michael
• Triangles are more reliable (distance to be large)
• Get manual landmarks from Jiun-hong’s

Jiun-hong’s pose normalize method

• On automatic landmarks_> should be nice
Ideas
• Bipartite matching
• Fit clusters into lines
• The use of bounding box
• Corners of 3D
• Use front and back info as a constrain
• How to evaluate the results

Using position, such as exhausting searching, can do symmetry and find matching points back and forth a couple of times

Learn: what is a good matching!!

• Give it some heads, learn from samples, what’s “good” matches
• Instead of use self’s constrains