**CS 5840: Computer Vision**

Fall 2016

Meets MW 6:05-7:20 PM, ENGR 107

**Syllabus:** PDF**Blackboard:** http://bb.uccs.edu

The gradebook and homework turn-in pages will be maintained in Blackboard.

**MATLAB access**

EAS students can install MATLAB on their own computer. More information can be found on this page from the EAS help desk. Students from other departments should contact the campus help desk (see this page).

MATLAB is also available on the computers in the Math Center (ENGR 233). Visit their page for schedule information. They even offer help with learning MATLAB!

**Textbooks**

R. Szeliski. Computer vision: algorithms and applications. Springer, 2010.

The textbook is available online for free as a PDF download at Richard Szeliski’s website, and is also available for purchase at the UCCS Bookstore.

S. Palmer. Vision Science: Photons to Phenomenology. MIT Press, 1999.

This is available electronically through the library.

**Interesting Links**

- Deep Art
- UCCS page with links to MATLAB tutorials
- Numerical Computing with MATLAB
- A Practical Introduction to MATLAB
- You Look Familiar: Unearthing the Face Within: Doris Tsao at TEDxCaltech
- Brian Greene : What's Beyond The Double Slit Experiment ?
- Quantum Mechanics / The Uncertainty Principle / Light particles
- Single slit interference
- Single slit diffraction simulation
- IARPA Mutli-View Stereo 3D Mapping Challenge
- Image Resizing by Seam Carving

**Class Schedule**

*Monday, August 22:*Introduction to Computer Vision*Wednesday, August 24:*Human Visual System; MATLAB Tutorial- Reading: Palmer sections 1.2.3-1.3.3
- Slides
- MATLAB Tutorial
*Monday, August 29:*Image Formation- Reading: Szeliski section 2.1
- Slides
*Wednesday, August 31:*Geometric Transformations- Reading: Szeliski section 2.1
- Slides
*Friday, September 2:*HW1 due*Monday, September 5:*Labor day holiday*Wednesday, September 7:*Filtering- Reading: Szeliski section 3.1-3.2
- Slides
*Monday, September 12:*Thinking in Frequencies- Reading: Szeliski section 3.3-3.4
- Slides
*Wednesday, September 14 and Monday, September 19:*Image Pyramids and Edges- Reading: Szeliski section 3.5, 4.2
- Paper: P. J. Burt and E. H. Adelson. The Laplacian Pyramid as a Compact Image Code. IEEE Transactions on Communications, 1983.
- Slides
*Wednesday, September 22:*Interest points and corners- HW2 due
- Reading: Szeliski section 4.1
- Slides
*Monday, September 26:*Feature matching and tracking- Reading: Szeliski section 4.1
- Paper: D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. IJCV 2004
- Slides
*Wednesday, September 28:*Lines, vanishing points and Hough transform- Reading: Szeliski section 4.3
- Slides
*Monday, October 3:*Introduction to machine learning, nearest neighbor classification*Wednesday, October 5:*Linear classification- HW3 due
- Reading: Lecture notes on linear classification from Stanford CS231N
- Slides
*Monday, October 10:*No class (Dr. Ventura at ECCV in Amsterdam)*Wednesday, October 12:*Midterm*Monday, October 17:*Robust Model Fitting- Reading: Szeliski section 6.1 and 6.2
- Slides
*Wednesday, October 19:*Optical Flow and Epipolar Geometry- Reading: Szeliski section 7.2
- Slides
*Monday, October 24:*Triangulation- Reading: Szeliski section 7.1
- Slides
*Wednesday, October 26:*Structure-from Motion and Bundle Adjustment- Reading: Szeliski section 7.4
- Slides
*Monday, October 31:*Stereo and “Shape from X”- Reading: Szeliski section 11.2, 11.3, 11.5, 12.1
- Slides
*Monday, November 7:*Eigenfaces- Reading: Szeliski section 14.2
- Slides
*Wednesday, November 9:*Machine Learning: Optimization- Reading:
- Lecture notes on optimization and backpropagation from Stanford CS231N
- Slides
*Monday, November 14 and Wednesday, November 16:*Neural Networks- Reading: Lecture notes (1, 2, 3, 4) on neural networks from Stanford CS231N
- Slides: Theory and Optimization
*Monday, November 21:*Convolutional Neural Networks- Reading: Lecture notes (1, 2, 3) on convolutional neural networks from Stanford CS231N
- Slides: Slides
*Wednesday, December 7:*Current and Future Topics in Computer Vision Research- Reading: Szeliski Chapter 15
- Slides: Slides