CSE327: Computer Vision

http://www.cs.sunysb.edu/~cse327

Instructor: Prof. Dimitris Samaras

Fall 2007: Tuesday and Thursday 3:50-5:10, SocBeh N118

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. Apart from basic theory we will look at applications of Computer Vision in Robotics, Graphics and Medicine. Topics this course will cover include:

 

1.  Image Formation
         Basic facts about light
         Anatomy of a camera

         Camera Response  Function

         Matting
2.  Image Noise
         Modeling image noise

         Convolution
         Smoothing images
3.  Image Features
         Edge Features
         Point Features, Corners
         The Hough Transform
4.  Model Fitting  
         Lines, Curves
         Deformation

         Robustness, Maximum Likelihood

         RANSAC

5.  Texture

        Scale

        Orientation

         Image Pyramids

6.  Image Patches

       The SIFT descriptor

       Template Matching

       PCA for Image Patches

7.  Perspective Projection

  Homogeneous Coordinates

  Image Warping

  Mosaics

8.  Multiple View Geometry
        Stereo Viewing and Reconstruction

   3D Range Scanning

9.  Motion
        Motion Capture
        Tracking in 2D and 3D    

10. Segmentation

        Grouping,

        Nearest Neighbors

11. Object Recognition
        Object representation

        Face Representation
        Classifiers
        Object Categories  

 

 

Intended Audience:

This course is intended for undergraduate 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. 

Grading:

There will be homeworks, a final project, two midterms and 2-3 10min quizes. Homeworks will be 40%, the project 35%, and the exams 35%. Weights are approximate and subject to change. You are expected to do homeworks (3 or 4) 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: October 23rd, 2007
You can have one sheet of paper with notes in the midterm and quizes.

Textbook:

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

Since the textbook covers only some of the topics in the course, readings and notes for the remaining topics will be posted on blackboard

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 Judiciary 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! The University has a relevant policy:

 

“Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Any suspected instance academic dishonesty will be reported to the Academic Judiciary. For more comprehensive information on academic integrity, including categories of academic dishonesty, please refer to the academic judiciary website at http://www.stonybrook.edu/uaa/academicjudiciary/  

                                                                                  

             Adopted by the Undergraduate Council September 12, 2006         

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

.