EE/CNS/CS 148 - Spring 2004
Lectures notes
| Lecture 1: |
Summary:
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Introduction to Recognition - problems to solve, applications. Brief description of the constellation model |
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03/30/04
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Notes
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Presentation (pdf,15.9MB) |
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| Lecture 2: |
Summary:
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Matched Filtering |
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03/30/04
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Notes
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(pdf,77KB)(ps,110KB) |
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Matlab Code:
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MatchedFilter.m ROC.m |
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| Lecture 3: |
Summary:
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Formation of an image - Lambertian surfaces/specular surfaces - RGB images - changes in contrast and brightness and invariance with respect to those - Principal components analysis: singluar values decomposition, computation of the subspace that best represents the data in a given number of dimensions. |
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04/06/04
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Notes
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(ps) (pdf) |
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Matlab Code:
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PCAspace.m PCA.m |
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| Lecture 4: |
Summary:
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Singular value decomposition and properties - Fisher Linear Discriminants. |
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04/08/04
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Notes:
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(ps) (pdf) |
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Matlab Code:
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fisherLD.m fisherDemo.m genData.m |
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Code and data:
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HRL-faces-Belhumeur/ |
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| Lecture 6: |
Summary:
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The constellation model - case with a single part. |
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04/15/04
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Notes:
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(ps) (pdf) |
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| Lecture 8: |
Summary:
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Constellation model - case with several parts. |
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04/22/04
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Notes:
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(ps) (pdf) |
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Paper:
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ECCV2000 paper by M.Weber (former PhD student in the Vision Lab) - (ps.gz) (pdf) |
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Matlab code:
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lecture8.m gaussian.m randnND.m |
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| Lecture 9: |
Summary:
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Constellation model - translation, rotation and scale invariance. |
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04/27/04
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Notes:
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(ps) (pdf) |
| Lecture 15: |
Summary:
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EM. |
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05/20/04
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Notes:
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(Clustering pdf) (EM pdf) (EM Code) (Draw Elipse Code) |
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