## Lecture notes with most views in computer vision

# Gaussian Noise Model-Introduction to Computer Vision-Lecture 04-Computer Science

Gaussian Noise Model, Gaussian Distribution, Removing Gaussian Noise, Gaussian Filter - 1D, Gaussian Filter - 2D, Blurring With Gaussian Filter, Blurring and Scale, Separability, Separable Filters, Integral Image, Box Filters, Edges and Filters, G...

# Edge in 1D-Introduction to Computer Vision-Lecture 05-Computer Science

Edge in 1D, Derivatives and Noise, Edges in 2D, Visualizing Derivatives, Derivative of Gaussian Filter, Derivative of Gaussian in 2D, Sobel Operators, Image Gradient, Computing Gradient, Thresholding the Gradient, Canny Edge Detector, Canny: Non-M...

# Aperture Problem-Introduction to Computer Vision-Lecture 07-Computer Science

Aperture Problem, Small Motion Analysis, SSD Approximation, Analysis of the Second Moment Matrix H, Refresher on Probability, Covariance Matrix, Rotation Matrices, Eigenvectors and Eigenvalues, Harris Corner Detector, Harris Detector: Practicaliti...