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Lecture 1: Introduction to Machine Vision

Lecture 5: TCC and FOR MontiVision Demos, Vanishing Point, Use of VPs in Camera Calibration

Lecture 17: Photogrammetry, Orientation, Axes of Inertia, Symmetry, Orientation

Lecture 12: Blob Analysis, Binary Image Processing, Green's Theorem, Derivative and Integral

Lecture 3: Time to Contact, Focus of Expansion, Direct Motion Vision Methods, Noise Gain

Lecture 14: Inspection in PatQuick, Hough Transform, Homography, Position Determination, Multi-Scale

Lecture 11: Edge Detection, Subpixel Position, CORDIC, Line Detection (US 6,408,109)

Lecture 10: Characteristic Strip Expansion, Shape from Shading, Iterative Solutions

Lecture 18: Rotation and How to Represent It, Unit Quaternions, the Space of Rotations

Lecture 21: Relative Orientation, Binocular Stereo, Structure, Quadrics, Calibration, Reprojection

Lecture 23: Gaussian Image, Solids of Revolution, Direction Histograms, Regular Polyhedra

Lecture 19: Absolute Orientation in Closed Form, Outliers and Robustness, RANSAC

Lecture 16: Fast Convolution, Low Pass Filter Approximations, Integral Images (US 6,457,032)

Lecture 4: Fixed Optical Flow, Optical Mouse, Constant Brightness Assumption, Closed Form Solution

Lecture 22: Exterior Orientation, Recovering Position & Orientation, Bundle Adjustment, Object Shape

Lecture 9: Shape from Shading, General Case - From First Order Nonlinear PDE to Five ODEs

Lecture 7: Gradient Space, Reflectance Map, Image Irradiance Equation, Gnomonic Projection

Lecture 8: Shading, Special Cases, Lunar Surface, Scanning Electron Microscope, Green's Theorem

Lecture 6: Photometric Stereo, Noise Gain, Error Amplification, Eigenvalues and Eigenvectors Review

Lecture 2: Image Formation, Perspective Projection, Time Derivative, Motion Field