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.
Offered By
University at Buffalo
The State University of New York
Computer Vision Basics
University at BuffaloAbout this Course
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Intermediate Level
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
Approx. 13 hours to complete
English
Subtitles: English
Skills you will gain
Computer VisionComputer ProgrammingMatlab
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
Approx. 13 hours to complete
English
Subtitles: English
Offered by
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.
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.
Syllabus - What you will learn from this course
4 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.
4 hours to complete
13 videos (Total 42 min), 2 readings, 4 quizzes
13 videos
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?30m
Related Fields of Computer Vision30m
MATLAB Basics5m
5 hours to complete
Color, Light, & Image Formation
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
5 hours to complete
4 videos (Total 32 min), 1 reading, 5 quizzes
1 reading
Resources (Optional): Color, Light, & Image Formation30m
3 practice exercises
Light Sources30m
Pinhole Camera Model30m
Digital Camera30m
3 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.
3 hours to complete
5 videos (Total 32 min), 1 reading, 3 quizzes
5 videos
Low-, Mid-, High-Level Vision1m
Low-Level Vision8m
Mid-Level Vision7m
High-Level Vision6m
1 reading
Resources (Optional): Low-, Mid- and High-Level Vision30m
2 practice exercises
Three-Level Paradigm30m
Low-Level Vision30m
2 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.
2 hours to complete
8 videos (Total 10 min), 2 readings, 2 quizzes
8 videos
Mathematical Preliminaries27s
Linear Algebra1m
Calculus45s
Probability Theory35s
Algorithms38s
Using Algorithms1m
Aligning RGB channels2m
2 readings
Resources (Optional): Mathematics for Computer Vision30m
Computer Vision Basics - Key Takeaways10m
1 practice exercise
Algorithms2m
Reviews
TOP REVIEWS FROM COMPUTER VISION BASICS
by HKAug 13, 2020
i really liked the course, but i wish that they would also help learn the programming in MATLAB a little, needs one extra week for the programming. Had to use external tools to learn the programming.
by LMAug 10, 2019
It is a good introduction course but I think some more demo coding for matlab in the first assignments will be a good thing so we don´t have to spend a lot of time on google and on trial and error.
by PSOct 12, 2019
Course was great ! And explained well but Matlab was not explained well. It's hard to complete week-4 assignment if you are not good at Matlab. Please provide python language for solving problems.
by PWMay 22, 2020
The course is fine, but it's too fundamental. Overall, it is more suit to personal who already had the fundamental in image processing knowledge. Else the course is a but higher level for others.
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Are there any prerequisites?
Learners should have basic programming skills and experience (understanding of for loops, if/else statements). 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), basic probability (random variables), and 3D co-ordinate systems & transformations.
Will I earn university credit for completing the Course?
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