605.661.81 - Computer Vision

Course Structure

The course materials are divided into modules which can be accessed by clicking Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted in the Course Outline. You should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

The following topics will be covered in this course.

• Image Formation
• Image Processing
• Edge Detection and Binary Images
• Feature Detection
• Image Alignment
• Camera Calibration
• Binocular Stereo and Multi-View Geometry
• Motion and Optical Flow
• Machine Learning Basics
• Introduction to Deep Learning
• Image Classification and Segmentation
• Object Detection and 3D Geometry
• Unsupervised and Generative Neural Networks
• Project Presentations

Course Goals

To gain understanding of classical computer vision techniques, deep learning methods, and principles of computer vision, and apply them to solving real world computer vision problems.

Course Learning Outcomes (CLOs)

• Understand the principles of computer vision including cameras, image representations, image processing, feature extraction/detection, stereo camera/3D geometry, camera calibration, object recognition, motion, segmentation, and deep learning principles.
• Apply the course material in a variety of vision applications including object detection, semantic segmentation, stereo camera calibration and pose estimation.
• Evaluate current research presented at leading computer vision conferences and journals.
• Develop the foundation to pursue research in computer vision.

Textbooks

Szeliski, R. (2022). Computer vision: Algorithms and applications. (2nd ed.). Springer. https://szeliski.org/Book/

Required Software

Python (3.8.13+)

Student Coursework Requirements

Python Notebooks (Optional)

This portion will consist of weekly optional Python notebooks used to reinforce the lecture and reading material corresponding to each module.

Assignments (30% of Final Grade Calculation)

Assignments will consist of 3 in-depth homework assignments going deeper into the subject matter. All python assignments should be submitted and include a readme.txt with the required python libraries and version numbers needed to run the notebook. Finally, if any outside material is used to complete the assignments, please reference those material.

All assignments are due according to the dates in the Calendar.

Late submissions will be reduced by one letter grade for each week late (no exceptions without prior coordination with the instructors).

Assignments are evaluated by the following grading elements:

1. The code runs successfully (10%)
2. Comments are provided that explain the code (20%)
3. The code accomplishes the objective and matches the expected output (55%)
4. Outside references are included (15%)

Assignments are graded as follows:

• 100–90 = A—All code runs successfully, ample comments are provided, the output matches the expected output and any references are included.
• 89–80 = B— All code runs successfully, some comments are provided, some of the outputs match the expected output and any references are included.
• 79–70=C— Some code runs successfully, few comments are provided, some of the outputs match the expected output and any references are included.
• <70=F— Major parts of the code do not run, few to no comments are provided, few of the outputs match the expected output and any references are included.

Preparation and Participation (20% of Final Grade Calculation)

You are responsible for carefully reading all assigned material and being prepared for discussion. The majority of readings are from the course text. Additional reading may be assigned to supplement text readings.

Post your initial response to the discussion questions by the evening of day 3 for that module week. Posting a response to the discussion question is part one of your grade for module discussions (i.e., Timeliness).

Part two of your grade for module discussion is your interaction (i.e., responding to classmate postings with thoughtful responses) with at least two classmates (i.e., Critical Thinking). Just posting your response to a discussion question is not sufficient; we want you to interact with your classmates. Be detailed in your postings and in your responses to your classmates' postings. Feel free to agree or disagree with your classmates. Please ensure that your postings are civil and constructive.

I will monitor module discussions and will respond to some of the discussions as discussions are posted. In some instances, I will summarize the overall discussions and post the summary for the module.

Evaluation of preparation and participation is based on contribution to discussions.

Preparation and participation is evaluated by the following grading elements:

Timeliness (50%)

Critical Thinking (50%)

Preparation and participation is graded as follows:

• 100–90 = A—Timeliness [regularly participates; all required postings; early in discussion; throughout the discussion]; Critical Thinking [rich in content; full of thoughts, insight, and analysis].
• 89–80 = B—Timeliness [frequently participates; all required postings; some not in time for others to read and respond]; Critical Thinking [substantial information; thought, insight, and analysis has taken place].
• 79–70 = C—Timeliness [infrequently participates; all required postings; most at the last minute without allowing for response time]; Critical Thinking [generally competent; information is thin and commonplace].

Course Project (30% of Final Grade Calculation)

A course project will be assigned several weeks into the course. The last week will be devoted to the course project. Teams should be between 2 and 3 members, however exceptions can be granted.

The course project is evaluated by the following grading elements:

1. Student preparation and participation (as described in Course Project Description) (40%)
2. Student technical understanding of the course project topic (as related to individual role that the student assumes and described in the Course Project Description) (20%)
3. Team preparation and participation (as described in Course Project Description) (20%)
4. Team technical understanding of the course project topic (as related to the Customer Team roles assumed by the students and the Seller Team roles assumed by the students and described in the Course Project Description) (20%)

Course Project is graded as follows:

• 100–90 = A—Student Preparation and Participation/ Team Preparation and Participation [individual/ team roles and responsibilities well defined and understood; individual/ team well versed in use of Adobe Connect; individual/ team work product(s) agreed to, well prepared and available to all team members/ instructors]; Student Understanding/ Team Understanding [rich in content; full of thought, insight, and analysis].
• 89–80 = B—Student Preparation and Participation/ Team Preparation and Participation [individual/ team roles and responsibilities well defined and understood; individual/ team well versed in use of Adobe Connect; individual/ team work product(s) agreed to and prepared]; Student Understanding/ Team Understanding [substantial information; thought, insight, and analysis has taken place].
• 79–70 = C—Student Preparation and Participation/ Team Preparation and Participation [individual/ team roles and responsibilities agreed to; individual/ team well versed in use of Adobe Connect; individual/ team work product(s) prepared]; Student Understanding/ Team Understanding [generally competent; information is thin and commonplace].

Exams (20% of Final Grade Calculation)

The midterm exam will be available in Module 9 and will cover modules 1-8. You will have one week to complete the exam and they will be due by 5PM exactly one week from their release. You may use the course text to complete the exams.

The exams are evaluated by the following grading elements:

1. Each part of question is answered (20%)
2. Writing quality and technical accuracy (30%) (Writing is expected to meet or exceed accepted graduate-level English and scholarship standards. That is, all assignments will be graded on grammar and style as well as content.)
3. Rationale for answer is provided (20%)
4. Examples are included to illustrate rationale (15%) (If a student does not have direct experience related to a particular question, then the student is to provide analogies versus examples.)
5. Outside references are included (15%)

Exams are graded as follows:

• 100–90 = A—All parts of question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [rich in content; full of thought, insight, and analysis].
• 89–80 = B—All parts of the question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [substantial information; thought, insight, and analysis has taken place].
• 79–70 = C—Majority of parts of the question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [generally competent; information is thin and commonplace].

Grading

I generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteria apply to both undergraduates and graduate students taking the course.

Grading Policy

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.