What Is Team Management: Strategies, Duties, Job, Career Outlook
January 21, 2025
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Instructors: Radhakrishna Dasari
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(1,812 reviews)
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Intermediate level
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
(1,812 reviews)
Recommended experience
Intermediate level
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
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
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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. * A free license to install MATLAB for the duration of the course is available from MathWorks.
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.
13 videos2 readings3 assignments1 app item1 plugin
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
4 videos1 reading3 assignments2 app items
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 videos1 reading2 assignments1 app item
In this lecture, we will discuss the Mathematics used in Computer Vision, which includes linear algebra, calculus, probability, and much more.
8 videos2 readings1 assignment1 app item
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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Reviewed on Jun 16, 2019
I would like to thank my course instructor. It is a short introductory course.It's interesting and have pushed me to further complete other courses in the specialization.
Reviewed on Oct 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.
Reviewed on Nov 28, 2019
This is a very basic overview to computer vision. It teaches how to use MATLAB very well. Assignments were challenging enough. Course content were not in-depth.
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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.
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