Introduction to Computer Vision

Syllabus

Learning Objectives

Upon completion of this course, students should be able to:

1. Recognize and describe both the theoretical and practical aspects of computing with images. Connect issues from Computer Vision to Human Vision
2. Describe the foundation of image formation and image analysis. Understand the basics of 2D and 3D Computer Vision.
3. Become familiar with the major technical approaches involved in computer vision. Describe various methods used for registration, alignment, and matching in images.
4. Get an exposure to advanced concepts, including state of the art deep learning architectures, in all aspects of computer vision.
5. Build computer vision applications with python and the pytorch framework.

Prerequisites

No prior experience with computer vision is assumed, although previous knowledge of visual computing or signal processing will be helpful. The following skills are necessary for this class:

• Data structures: You’ll be writing code that builds representations of images, features, and geometric constructions.
• Programming: Projects are to be completed and graded in Python. All project starter code will be in Python. TA’s will support questions about Python. If you’ve never used Python that is OK, as long as you have programming experience.
• Math: Linear algebra, vector calculus, and probability. Linear algebra is the most important and students who have not taken a linear algebra course have struggled in the past.

Grading

This project is heavily project-based, but there will be graded quizzes administered through canvas. The grading distribution is:

Late policy for this course will be 10% per day late, as discussed on the first day of class and clarified on Piazza.

Academic Integrity

Academic dishonesty will not be tolerated. This includes cheating, lying about course matters, plagiarism, or helping others commit a violation of the Honor Code. Plagiarism includes reproducing the words of others without both the use of quotation marks and citation. Students are reminded of the obligations and expectations associated with the Georgia Tech Academic Honor Code and Student Code of Conduct, available online at www.honor.gatech.edu.

You are expected to implement the core components of each project on your own, but the extra credit opportunties often build on third party data sets or code. That’s fine. Feel free to include results built on other software, as long as you are clear in your handin that it is not your own work.

You should not view or edit anyone else’s code. You should not post code to Piazza, except for starter code / helper code that isn’t related to the core project.

Important Links:

• Piazza. This should be your first stop for questions and announcements.
• Gradescope will be used to hand in assignments.

Contact Info and Office Hours:

If possible, please use Piazza to ask questions and seek clarifications before emailing the instructor or staff.

Acknowledgements

The materials from this class rely significantly on slides prepared by other instructors, especially James Hays, Derek Hoiem, Svetlana Lazebnik, and Judy Hoffmann. Each slide set and assignment contains acknowledgements. Feel free to use these slides for academic or research purposes, but please maintain all acknowledgements.

Covid 19 Information

The fall semester 2020 is especially challenging due to the Covid-19 pandemic. Even though CS 6476 will be taught remotely, please take note of the information below.  The most up-to-date information on Covid-19 is on the TECH Moving Forward website.

Expectations and Guidelines

Each of us has a responsibility to ourselves and our fellow Yellow Jackets to be mindful of our shared commitment.

• We are all required to wear a face covering while inside any campus facilities/buildings, including during in-person classes, and to adhere to social distancing of at least 6 feet. Information on the Institute’s policy on face coverings.
• Students are expected to sit in assigned seats and to come to class only on days that are assigned to them.
• Papers, projects, tests, homework, and other assignments will only be accepted in electronic form unless the assignment is a physical artifact. 

Additional information is available in the Student Guidebook.

Instructor Illness or Exposure to Covid-19

During the fall 2020 semester, some faculty members may be required to quarantine due to exposure or isolate due to a Covid-19 diagnosis. Some disruption to classes or services is inevitable, but Georgia Tech is making every effort to ensure continuity of operations. As is the case in any semester, faculty may cancel a class if they have an illness or emergency situation and cover any missed material at their own discretion. If we need to cancel a class, we will notify students as early as possible.

Student Illness or Exposure to Covid-19

During the semester, you may be required to quarantine or self-isolate to avoid the risk of infection to others.  Quarantine is the separation of those who have been exposed to someone with Covid-19 but who are not ill; isolation is the separation of those who have tested positive for Covid-19 or been diagnosed with Covid-19 by symptoms.

If you have not tested positive but are ill or have been exposed to someone who is ill, please follow the Covid-19 Exposure Decision Tree for reporting your illness.

During the quarantine or isolation period you may feel completely well, ill but able to work as usual, or too ill to work until you recover.

Unless you are too ill to work, you should be able to complete your remote work while in quarantine or isolation.

If you are ill and unable to do course work this will be treated similarly to any student illness. The Dean of Students will have been contacted when you report your positive test or are told that it is necessary to quarantine and will notify your instructor that you may be unable to attend class events or finish your work as the result of a health issue. Your instructor will not be told the reason. We have asked all faculty to be lenient and understanding when setting work deadlines or expecting students to finish work, and so you should be able to catch up with any work that you miss while in quarantine or isolation. Your instructor may make available any video recordings of classes or slides that have been used while you are absent, and may prepare some complementary asynchronous assignments that compensate for your inability to participate in class sessions. Ask your instructor for the details.

CARE Center, Counseling Center, Stamps Health Services, and the Student Center

These uncertain times can be difficult, and many students may need help in dealing with stress and mental health. The CARE Center and the Counseling Center, and Stamps Health Services will offer both in-person and virtual appointments. Face-to-face appointments will require wearing a face covering and social distancing, with exceptions for medical examinations. Student Center services and operations are available on the Student Center website. For more information on these and other student services, contact the Vice President and Dean of Students or the Division of Student Life.

Accommodations for Students at Higher Risk for Severe Illness with Covid-19

Students may request an accommodation through the Office of Disability Services (ODS) due to 1) presence of a condition as defined by the Americans with Disabilities Act (ADA), or 2) identification as an individual of higher risk for Covid-19, as defined by the Centers for Disease Control (CDC). Registering with ODS is a 3-step process that includes completing an application, uploading documentation related to the accommodation request, and scheduling an appointment for an “intake meeting” (either in person or via phone or video conference) with a disability coordinator.

 If you have been approved by ODS for an accommodation, I will work closely with you to understand your needs and make a good faith effort to investigate whether or not requested accommodations are possible for this course. If the accommodation request results in a fundamental alteration of the stated learning outcome of this course, ODS, academic advisors, and the school offering the course will work with you to find a suitable alternative that as far as possible preserves your progress toward graduation.

Course Homeworks/Assignments/Papers

All course assignments will be submitted electronically via Canvas.

Course Attendance Structure:

Class sessions for CS 6476 will take place remote but synchronously. You are encouraged to attend class duting the assigned class times (Monday and Wednesday, 5pm-6.15pm) and re-review the video snippets when they become available.