Computer Science and Engineering

Computer Vision

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CSE 589 and 489

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Syllabus

CSE 589 or 489, Computer Vision, 3 cr, 3 cl hrs

Prerequisite: Programming skills in one or more of the following programming languages:

or other programming languages by request and approval.

Objective:   Introduce the student to the concepts of computer vision: what is meant, how it is done, and its current limitations. In-depth exercises will help the student to become familiar with the algorithms that are being used.

Course Catalog Description:   None

Content: Students will be exposed to the details of computer vision. They will cover the following:

  1. Image acquisition and manipulation,
  2. Basic features in images,
  3. Stereo and image sequence processing,
  4. Generating models from multiple image views,
  5. Feature aggregation for object characterization, and
  6. Object identification.

Class Goals --
  1. Group problem solving for technical problems,
  2. Development and coordination of individual and large-scale projects,
  3. Writing a technical paper.

In addition to the specific topics listed above, current developments and student or instructor interests may drive the selection of other topics to be covered in the course.

Assignments:   Assignments will reinforce lecture concepts and demonstrate application of programming and critical thinking skills. Collaboration is encouraged, but you must give credit where credit is due. All assignments must be done independently and written (typed) in your own words.

Quizzes:   Daily quizzes may be used to reinforce concepts, check student comprehension, and initiate discussion.

Examinations:   There will be no examinations.

Projects:   All files are subject to inspection by the instructor. Projects are to be submitted electronically. Submission will be to jholten@nmt.edu; the subject must be your last name followed by the project subject (e.g. "Holten- Image Acquisition").

All programming projects for this class should be written using an easily readable and well-organized coding style.

Plagiarism Policy:   Students are encouraged to discuss homeworks and projects with others. Ideas from outside sources should be properly credited to their sources. However, everything that is turned in for each assignment and/or miniproject must be your own work. In particular, it is not acceptable to: Copy in part or in totality another person's assignment and submit it as your own work; Get someone else to do all or a part of the work for you; Submit the work of others as your own work. When the work of others is included in your work the sources should be adequately cited for easy reference, otherwise these acts are plagiarism and will not be tolerated in this course.

Attendance Policy:   Students are encouraged to attend all classes. Attendance will count toward participation.

Grades:   The tentative percentage of points allocated to the major graded components are shown below. Student grades will be determined based on a straight scale.

Instructor Discretion:   The instructor reserves the right to modify policies to improve the execution of this course.

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