Fundamentals of Computer Vision    COMP 558
Fall 2019 
  ENGMD 279, Wed. & Fri. 2:35-3:55

Course co-developed with Prof. Michael Langer


Instructors

Prof. Kaleem Siddiqi     
Office:        McConnell Engineering, 420
Tel:             514-398-3371
Email:         siddiqi@cim.mcgill.ca
Office Hrs.:      Fridays 9:00-10:30
Teaching Assistants

Tabish Syed        Email:      tabish.syed@mail.mcgill.ca
Office Hours:      Thursdays, 16:00-18:00, TR 3110

Yiran Mao           Email:     yiran.mao@mail.mcgill.ca
Office Hours:      Mondays, 16:00-18:00, TR 3110

Announcements Resources and other links

Lecture Schedule

Introduction

  1. Course overview

2D Vision: Image processing and representation

  1. RGB
  2. Image filtering
  3. Edge detection
  4. Least Squares Estimation: lines & vanishing points
  5. Robust Estimation: Hough & RANSAC
  6. Scale space (Gaussian)
  7. Features 1: corners, intro to histograms
  8. Features 2: histogram-based (SIFT, HOG)
  9. Features 3: learned features (CNN's)
  10. Image Registration 1: translation (Lucas-Kanade)
  11. Image Registration 2: affine
  12. Tracking: histogram-based

IN CLASS MIDTERM EXAM - Friday October 18th

3D Vision

  1. Linear perspective, camera translation
  2. Vanishing points, motion field for camera rotation
  3. finite camera rotation, homogeneous coordinates
  4. Camera extrinsics and intrinsics
  5. Least Squares methods (eigenspaces, SVD)
  6. Camera Calibration, Homographies 1: plane in 2 views
  7. Homographies 2: image stitching, rectification
  8. Stereo and Epipolar Geometry 1
  9. Stereo and Epipolar Geometry 2
  10. Stereo correspondence
  11. Lighting and reflectance
  12. Active contours
  13. RGBD Cameras & Point Clouds