ANNOUNCEMENTS

  • Course Outline
  • All course materials (lecture notes, slides, lecture recordings, exercises, etc) are on mycourses.

LECTURES

Part 1: 2D Vision

  1. Introduction
  2. RGB
  3. Image filtering
  4. Edge detection
  5. Least Squares Estimation: lines & vanishing points
  6. Robust Estimation: Hough & RANSAC
  7. Features 1: corners
  8. Image Registration (Lucas-Kanade)
  9. Scale space (Gaussian)
  10. Tracking using histogram
  11. Features 2: histograms (SIFT, HOG)
  12. Features 3: CNN's
  13. Object detection and localization
  14. Segmentation

 

Part 2: 3D Vision

  1. Linear perspective, Vanishing points
  2. Rotations, homogeneous coordinates
  3. Camera extrinsics and intrinsics
  4. Least Squares methods (eigenspaces, SVD)
  5. Camera Calibration
  6. Homographies: image stitching, rectification
  7. Stereo and Epipolar Geometry
  8. Stereo correspondence
  9. Photography
  10. RGBD Cameras