## Machine Learning for Computer Vision @ MVA Master

**Lecture notes**

**Lecture 1: Introduction to classification**

**Lecture 2: Logistic Regression**[assignment 1]

**Lecture 3: Support Vector Machines**

**Lecture 4: Boosting/Ensemble Methods**[assignment 2]

**Lecture 5: Generative Models, EM algorithm**

**Lecture 6: Graphical Models, DPMs**[assignment 3]

**Lecture 7: Fast detection with DPMs**

**Lecture 8: Markov Random Fields**

**Deliverable: Object detection**

[code] [pdf] [data]

## Vision lectures @ IPAM-UCLA summer school

Video recordings are available from hereIntroduction to linear image processing

Introduction to non-linear image processing

Introduction to motion correspondence

Interest point detectors and descriptors

Statistical shape models

Fast Deformable Part Model detection using Branch-and-Bound

## Computer Vision @ ECP(2009-)

Log in here## Signal Processing @ ECP (2009-)

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