By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence. Topics include color, light and image formation; early, mid- and high-level vision; and mathematics essential for computer vision. Learners will be able to apply mathematical techniques to complete computer vision tasks.
This course is ideal for anyone curious about or interested in exploring the concepts of computer vision. It is also useful for those who desire a refresher course in mathematical concepts of computer vision. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables).
Material includes online lectures, videos, demos, hands-on exercises, project work, readings and discussions. Learners gain experience writing computer vision programs through online labs using MATLAB* and supporting toolboxes.
This is the first course in the Computer Vision specialization that lays the groundwork necessary for designing sophisticated vision applications. To learn more about the specialization, check out a video overview at https://youtu.be/OfxVUSCPXd0.
* A free license to install MATLAB for the duration of the course is available from MathWorks.
This course is part of the Computer Vision Specialization
Computer Vision Basics
Offered By
University at Buffalo
The State University of New York
About this Course
What you will learn
Understand what computer vision is and its goals
Identify some of the key application areas of computer vision
Understand the digital imaging process
Apply mathematical techniques to complete computer vision tasks
Skills you will gain
Computer VisionComputer ProgrammingMatlab
Syllabus - What you will learn from this course
Week
13 hours to complete
Computer Vision Overview
In this module, we will discuss what computer vision is, the fields related to it, the history and key milestones of it, and some of its applications.
14 videos (Total 44 min), 2 readings, 4 quizzes
14 videos
Meet Jeff Bier1m
Meet Jungsong Yuan, Ph.D.24s
What is Computer Vision?6m
Why Computer Vision?40s
Related Fields of Computer Vision4m
Relevant Fields56s
Computer Programming & Computer Vision1m
Computer Vision Awareness1m
Timelines & Milestones8m
Computer Vision Progression1m
Computer Vision Applications8m
CV Applications4m
CV Impact in the Field of Augmented Reality1m
2 readings
Resources (Optional): Computer Vision Overview30m
REQUIRED - MATLAB Resources10m
3 practice exercises
What is Computer Vision?2m
Related Fields of Computer Vision2m
MATLAB Basics
Week
23 hours to complete
Color, Light, & Image Formation
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
4 videos (Total 25 min), 1 reading, 5 quizzes
1 reading
Resources (Optional): Color, Light, & Image Formation30m
3 practice exercises
Light Sources4m
Pinhole Camera Model2m
Digital Camera2m
Week
32 hours to complete
Low-, Mid- & High-Level Vision
In this module, we will discuss the three-level paradigm of computer vision that was proposed by David Marr. We will also discuss low, mid, and high level vision.
5 videos (Total 8 min), 1 reading, 3 quizzes
5 videos
Low-, Mid-, High-Level Vision1m
Low-Level Vision55s
Mid-Level Vision1m
High-Level Vision1m
1 reading
Resources (Optional): Low-, Mid- and High-Level Vision30m
2 practice exercises
Three-Level Paradigm2m
Low-Level Vision2m
Week
42 hours to complete
Mathematics for Computer Vision
In this lecture, we will discuss the Mathematics used in Computer Vision, which includes linear algebra, calculus, probability, and much more.
7 videos (Total 8 min), 2 readings, 2 quizzes
7 videos
Mathematical Preliminaries27s
Linear Algebra1m
Calculus45s
Probability Theory35s
Algorithms38s
Using Algorithms1m
2 readings
Resources (Optional): Mathematics for Computer Vision30m
Computer Vision Basics - Key Takeaways10m
1 practice exercise
Algorithms2m
Instructors
Radhakrishna Dasari
InstructorDepartment of Computer Science
Junsong Yuan
Associate Professor and Director of Visual Computing LabComputer Science and Engineering
About University at Buffalo
The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs.
About The State University of New York
The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe.
About the Computer Vision Specialization
This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes.
The specialization is taught in MATLAB* using computer vision and supporting toolboxes. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables).
To learn more, check out a video overview at https://youtu.be/OfxVUSCPXd0.
* A free license to install MATLAB for the duration of the course is available from MathWorks.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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