Computer Vision

// computer vision · 17 lessons · 16 live demos

[computer vision]

Learn computer vision by instrumenting real pixels. Every lesson opens with a live demo — point your camera at it, drag the knobs, watch the operator fire — and the math sits right beside the signal it transforms.

start lesson 01 → glossary
01

Foundations

  1. #00

    What is Computer Vision?

    Teaching Machines to See

    in
    light
    op
    overview
    out
    meaning
  2. #01 ▸ demo

    Pixels & Color Spaces

    The Digital Image

    in
    RGB
    op
    color-space
    out
    channels
  3. #02 ▸ demo

    The Pinhole Camera Model

    How Cameras See

    in
    3D
    op
    projection
    out
    2D
  4. #03 ▸ demo

    Camera Matrix & Projection

    The Math of Seeing

    in
    3D
    op
    K·[R|t]
    out
    pixels
02

Image Filtering

  1. #04 ▸ demo

    Convolution

    The Foundation of Filtering

    in
    image
    op
    kernel ⊛
    out
    filtered
  2. #05 ▸ demo

    Edge Detection

    Finding Boundaries

    in
    image
    op
    Sobel
    out
    edges
  3. #06 ▸ demo

    Noise Reduction

    Cleaning Up Images

    in
    noisy
    op
    Gaussian
    out
    smooth
03

Feature Detection

  1. #07 ▸ demo

    Corner Detection

    Finding Interest Points

    in
    image
    op
    Harris
    out
    corners
  2. #08 ▸ demo

    Blob Detection

    Finding Regions

    in
    image
    op
    LoG
    out
    blobs
  3. #09 ▸ demo

    Thresholding

    Binary Decisions

    in
    gray
    op
    Otsu
    out
    binary
04

Geometry & Transforms

  1. #10 ▸ demo

    Image Transformations

    Rotate, Scale, Warp

    in
    image
    op
    affine
    out
    warped
  2. #11 ▸ demo

    Homography

    Plane-to-Plane Mapping

    in
    image
    op
    H 3×3
    out
    rectified
  3. #12 ▸ demo

    Contour Detection

    Finding Shapes

    in
    binary
    op
    trace
    out
    contours
05

3D Vision

  1. #13 ▸ demo

    Stereo Vision & Depth

    Seeing in 3D

    in
    L + R
    op
    Z = fb/d
    out
    depth
  2. #14 ▸ demo

    Epipolar Geometry

    The Geometry of Two Views

    in
    point
    op
    F·p
    out
    line
06

Applications

  1. #15 ▸ demo

    Color Tracking

    Following Objects

    in
    RGB
    op
    HSV thresh
    out
    mask
  2. #16 ▸ demo

    Face Detection

    Finding Faces

    in
    image
    op
    cascade
    out
    boxes