Name: Prof. John Gauch
Office: 518 JBHT
Office Hours: Mon, Wed, Fri 9:45-10:45 and 1:45-2:45
The objective of this course is to give students a hands-on introduction to
the fundamentals of computer vision. Topics include: image formation,
image processing, feature detection and matching, segmentation, feature-based
alignment, structure from motion dense motion estimation, image stitching,
stereo correspondence, 3D shape reconstruction, and object recognition.
Upon completion of this course, students should be prepared to read current
papers in computer vision and to undertake research in this area.
Prerequisites: Programming experience in C/C++ in a UNIX environment, some
background in digital image processing or computer graphics.
"Computer Vision: Algorithms and Applications" by Richard Szeliski,
which is available in PDF format at http://szeliski.org/Book.
We will also use the open source computer vision library OpenCV at
Final grades in this class will be determined by a weighted average
of programming project scores and exam scores as follows:
We use the following scale to assign final grades:
There will be 6-8 relatively large programming projects that
will integrate material taught in the course. The project requirements
and due dates will be posted on the class website.
The programming projects will be graded according to the following scale:
Programming projects must be submitted electronically by midnight of the
due date specified in the project description. Projects which are submitted
after the due date lose 10% per day for up to 3 days late. Projects more
than 3 days late will not be accepted and will receive a grade of ZERO.
Weekends count as 1 day. Partial credit will be given for programs which
compile but which are not complete. Starting early on programming projects
is strongly encouraged.
There will be two exams in this class. One midterm exam and a
comprehensive final exam. All exams will be closed book, but each student
will be allowed to bring in a single 8.5 by 11 sheet of notes.
Calculators will not be needed or allowed. Make up exams will only be
allowed under exceptional circumstances (e.g., a note from your doctor).
As a core part of its mission, the University of Arkansas provides
students with the opportunity to further their educational goals through
programs of study and research in an environment that promotes freedom
of inquiry and academic responsibility. Accomplishing this mission is
only possible when intellectual honesty and individual integrity prevail.
Each University of Arkansas student is required to be familiar with and
abide by the University's 'Academic Integrity Policy' at honesty.uark.edu.
Students with questions about how these policies apply to a particular
course or assignment should immediately contact their instructor.
The following policies will apply to this class.
Homework and Programming Projects:
Violations of the policies above will be reported to the Provost's
office and may result in a ZERO on the exam or programming project,
an F in the class, or suspension from the university, depending on the
severity of the violation.
If any member of the class has a documented disability and needs
special accommodations, the instructor will work with the student to
provide reasonable accommodation to ensure the student a fair opportunity
to perform in this class. Please advise the instructor of the disability
and the desired accommodations within the first week of the semester.
If the university is officially closed, class will not be held. When
the university is open, you are expected to make a reasonable effort to
attend class, but not if you do not feel that you can get to campus safely.
Assignment due dates will be postponed in case of inclement weather.
Many types of emergencies can occur on campus; instructions for specific
emergencies such as severe weather, active shooter, or fire can be found at
Severe Weather (Tornado Warning):
Violence / Active Shooter: