CSE 559: Computer Vision, Spring 2012

Lectures: Monday/Wednesday, 1:00-2:30pm, Room: McDonnell 362 Contact Info:: Robert Pless, pless (a) wustl edu Office Hours: 518 Lopata Hall, Tuesday 3:30-4:30pm, or by appointment. Textbook: In lieu of a(n expensive) normal textbook for this class, we will use some of Rick Szeliski's fantastic textbook, and occasional other readings. Course Structure and Grading: The course will have 3 projects, two in class written quizes and a final project. Projects will be turned by preparing and sharing a webpage.

Announcements

Syllabus

• Introduction: Lecture Notes. Reading: Szeliski, Chapters 1
• Mon. Jan 23: Image Formation -- Camera Model
  1. Reading: Szeliski, Chapter 2.1.
  2. Lecture Notes
  3. PR-2 Calibration
  4. matlab code
• Wed. Jan 25: Image Formation -- Homographies, Camera Rotations, Re-Projection Error
  1. Reading: Szeliski, Chapter 2.1.
  2. Lecture Notes
  3. Matlab Code: calibration Example, nonlinear error function
• Image Processing -- Filtering
  1. Reading: Szeliski, Chapter 3.2.
  2. Lecture Notes
• PROJECT 1
• Image Processing -- Filter / Fourier Transforms
  1. Reading: Szeliski, Chapter 3.4
  2. Lecture Notes
  3. Matlab Code: Fourier Examples
• Image Processing -- Template Matching and Image Pyramids
  1. Reading: Szeliski, Chapter 3.5.
  2. Lecture Notes
  3. Matlab Code: hybrid image skeleton
• Feature Detection and Matching (SIFT). Feb. 8, 2012
  1. David Lowe's SIFT paper.
  2. Approx Lecture Notes
  3. Reading: Szeliski, Chapter 4.1.1-4.1.2
• Image Stitching, RANSAC, homographies form a group. Feb. 13, 2012
  1. Approx Lecture Notes
  2. Reading: Szeliski, Chapter 9.1-9.1.5.
• PROJECT 2
• Camera motion and the Epipolar constraint
  1. Approx Lecture Notes
  2. Reading: Szeliski, Chapter 7.1 - 7.2.1.
• Feb 20: Stereo Matching and How the Kinect Works
  1. Approx Lecture Notes
  2. Reading: Szeliski, Chapter 7.1 - 7.2.1.
• Feb 22: Video, Image Motion and Optic Flow.
  1. Approx Lecture Notes
• egomotion
  1. Approx Lecture Notes
• SAMPLE QUIZ: link!.
• Moving towards video, but starting with analysis of multiple pictures: Eigen-images, Eigen Faces + Eigen Scenes.
  1. Reading: Szeliski, Chapter 14.2.1
  2. Approx Lecture Notes
  3. matlab code, getfaces.m
• Monday March 19, Special Guest Lecture, Viktor Gruev, on Polarization Imaging.
• Wednesday March 21, Special Guest Lecture, Kilian Weinberger, on Manifold Learning.
• PROJECT 3, due 11:59 pm, wednesday April 11.
• Monday March 26, Dynamic Textures,
  1. matlab code
• Wednesday March 28, Face Detection
  1. Reading: Szeliski, Chapter 14.1.1
  2. matlab code, getfaces.m
  3. Approx Lecture Notes
• Monday , Active Shape Models
  1. Reading: Szeliski, Chapter 14.2.2
  2. Approx Lecture Notes
• Wednesday , Active Appearance Models
  1. Approx Lecture Notes (same as previous class).
• Monday, KLT Tracking (as proxy for Fitting Active Appearance Models)
  1. Approx Lecture Notes
  2. Material also in Szeliski, Chapter 8.1.3, but somewhat out of context...
• Wednesday, PCA, CCA and Time-lapse imagery.
  1. Approx Lecture Notes
• Monday, Photometric Stereo (lecture by Austin Abrams)
  1. Approx Lecture Notes
  2. matlab code and pictures
• Wednesday, Intrinsic Images
  1. Approx Lecture Notes
• Future of Computer Vision:
  1. http://mattrichardson.com/Descriptive-Camera/