16-720 Computer Vision Carnegie Mellon University Robotics Institute

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Lecture Slides

Introduction (pdf)

Cameras & Camera Geometry (pdf)

Filtering, Edge Detection, Frequency Analysis, Interest Point Operators (pdf)

Frequency analysis, pyramids, texture analysis, applications (pdf)

Interest Points and Scale Invariance (pdf)

SIFT: Scale Invariant Feature Transform (pdf)

Interest Point Detectors and Affine Invariance (pdf)

Geometry of Multiple Views: 2- and 3-View Geometry (pdf)

Stereo (pdf)

Structure from Motion (pdf)

General Case: Projective Reconstruction (pdf)

Non-Linear Refinement: Bundle Adjustment (pdf)

Rotation case: Panoramas, mosaicing, image stitching (pdf)

Motion, Tracking and Optical Flow I (pdf)

Motion, Tracking and Optical Flow II (pdf)

Shading + Color (pdf)

Segmentation & Fitting I (pdf)

Segmentation & Fitting II, Clustering, Mean Shift (pdf)

Recognition I (pdf)

Recognition by discriminative classifiers on local histogram representations (pdf)

Additional Materials

Matlab Tutorial Files [Basic Operations | Programming | Working with Images ], Materials used in recitation [ZIP]

Matlab Primer [ps|pdf]

Math Primer [ps | pdf ], Figures [ps | pdf]

Andrew Moore's tutorials: [Intro to probability (first part only) | Basics of probability densities | Gaussian distributions]