Syllabus ----- Schedule

CSCI-631 Foundations of Computer Vision Syllabus

Catalogue Description

An introduction to the underlying concepts of computer vision and image understanding. The course will consider fundamental topics, including image formation, edge detection, texture analysis, color, segmentation, shape analysis, detection of objects in images and high level image representation. Depending on the interest of the class, more advanced topics will be covered, such as image database retrieval or robotic vision. Programming assignments are an integral part of the course.  Credit 3 (Fall,Spring)

Course Outcomes

• Students will demonstrate a thorough knowledge of fundamental concepts pertaining to computer vision 
• Students will be able to implement fundamental spatial filtering algorithms using correlation and convolution techniques.
• Students will be able to segment objects in an image based on texture and color features.
• Students will design and implement a computer vision project utilizing the concepts taught in this course and evaluate their approach, analyze their results and present their research in class.
• Students will advance their research and analytical skills.

Instructor Contact

• Roger S. Gaborski, Ph.D.
• Office: 70 - 3647
• Phone: N/A
• email: rsg@cs.rit.edu
• website: www.cs.rit.edu/~rsg
• 
  

Course Policies

Homework assignments are assigned, collected and graded. This work must be done independently. Discussion of the problem with other individuals is not allowed unless stated in writing on homework assignment. Email all completed homework assignments to the course account.

Late homework - A 25% penalty will be assigned to homeworks not received by 8am on the day the homework is due, but received within 24 hours after the due date. 

For example, if the homework is due April 1st at 8am, any homeworks received after  8:01am on April 1st and  before 8am on April 2nd will be assigned a 25% penalty. 

Homeworks are not accepted if more than 24 hours late.

The computer vision project will give you the opportunity to extend what you have learned in class and apply your knowledge to an interesting and challenging problem. Your project must extend and go beyond the material presented in class. There must be a research component. You must use the MATLAB programming language. If you simply apply what we have covered in class or homework assignments to the project you will receive a failing grade. For example, if you use texture analysis in your project you cannot simply use the co-occurrence texture technique that we cover in class. You must research the texture literature and find a better texture analysis method. The following table lists several project ideas.  

Required Materials

• Gonzales, Woods and Eddins, Digital Image Processing with MATLAB, 2009
• MATLAB Programming Environment

Additional Resources

• N/A

Grading

CS Common Course Policies Include:

• Rescheduling an Exam
• Course Withdrawal
• Disability Services
• Academic Integrity

updated: Monday April 16 12:08:00 EDT 2012