CSE527: Introduction to Computer Vision

http://www.cs.sunysb.edu/~cse527

Instructor: Prof. Dimitris Samaras

Spring 2007: Mondays and Wednesdays 6:50-8:10 in CS 2129

Course Syllabus

The aims of this course are to provide an understanding of the fundamentals of Computer Vision and to give a glimpse in the state-of-the-art, at a moment when the field is achieving "critical mass" and has started having significant commercial applications. Topics this course will cover include:

1.  Image Formation          Basic facts about light          Anatomy of a camera 2.  Camera Geometry          Homogenous coordinates, Mosaics          Euclidean, Affine and projective transformations          Perspective, Orthographic, Weak Perspective          The consequences of various camera models Camera Calibration 3. Illumination Shading, Shadows, Interreflections, Reflectance properties of materials 4. Image Noise          Modeling image noise          Smoothing images 5.  Image Features          Edge Features          Point Features          The Hough Transform 6.  Model Fitting           Lines, Curves           Deformable Models Robustness, Maximum Likelihood

7. Texture Scale, Orientation, Fourier Transforms 8. Multiple View Geometry - Stereo     The epipolar constraint     The fundamental matrix     Mosaics     Computing correspondences     Recovering depth from stereo 9. 3D Shape from X     Shape from Shading, Photometric Stereo     Shape from Texture     Range Data 10. Motion Motion detection & Optical flow, Structure from Motion, Image-Based Rendering 11. Segmentation Grouping, Probabilistic Fitting, Nearest Neighbors, EM, Tracking, Kalman Filtering 12. Object Recognition Object representation, Face Representation Probabilistic Classifiers Appearance-based methods

Intended Audience:

This course is intended for graduate students with interests in all areas of Visual Computing, such as Computer Vision, Computer Graphics, Visualization, Biomedical Imaging, Robotics, Virtual Reality, Computational Geometry. Prerequisites include a foundation in Linear Algebra and Calculus, and the ability to program, preferably in C/C++.

Grading:

There will be homeworks, a final project, and a midterm and 2-3 15min quizes. Homeworks will be 35%, the project 30%, and the exams 35%. Weights are approximate and subject to change. You are expected to do homeworks (4 or 5) by yourselves. Even if you discuss them with your classmates, you should turn in your own code and write-up.  Final projects can be done by one or two people. Two people projects will be scaled accordingly.

Midterm date: April 9, 2007
You can have one sheet of paper with notes in the midterm and quizes.

Textbook:

Computer Vision: A Modern Approach, Forsyth and Ponce, Prentice Hall 2002.
Class notes and a collection of additional readings from journals and conference proceedings will be available through Blackboard.

(Optional)  Introductory Techniques for 3-D Computer Vision by E. Trucco and A. Verri,
Prentice Hall, Upper Saddle River, N.J., 1998

Academic misconduct policy:

Don't cheat. Cheating on anything will be dealt with as academic misconduct and handled accordingly. I won't spend a lot of time trying to decide if you actually cheated. If I think cheating might have occurred, then evidence will be forwarded to the University's Academic Misconduct Committee and they will decide. If cheating has occured, an F grade will be awarded. Discussion of assignments is acceptable, but you must do your own work. Near duplicate assignments will be considered cheating unless the assignment was restrictive enough to justify such similarities in independent work. Just think of it that way: Cheating impedes learning and having fun. The labs are meant to give you an opportunity to really understand the class material. If you don't do the lab yourself, you are likely to fail the exams. Please also note that opportunity makes thieves: It is your responsibility to protect your work and to ensure that it is not turned in by anyone else. No excuses!

Disability note:

If you have a physical, psychological, medical or learning disability that may impact on your ability to carry out assigned course work, I would urge that you contact the staff in the Disabled Student Services office (DSS), Room 133 Humanities, 632-6748/TDD. DSS will review your concerns and determine, with you, what accommodations are necessary and appropriate. All information and documentation of disability is confidential.

Contact info:

    D. Samaras, Tel. 631-632-8464
    email: samaras@cs.sunysb.edu
    Office Hours: Tue., Wed 1:30pm to 3pm, or by appointment
                         Computer Science room 2429

•     TA : Lei Zhang
• email:
• Office Hours: Mon, Wed 2:00pm to 3:00pm, or by appointment

CS 2110 TA office