Computer Vision Basics
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Computer Vision Basics
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What you'll 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'll gain
Tools you'll learn
Details to know
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There are 4 modules in this course
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.
What's included
13 videos2 readings4 assignments
13 videos•Total 42 minutes
- Meet Jeff Bier•1 minute
- Meet Jungsong Yuan, Ph.D.•0 minutes
- What is Computer Vision?•7 minutes
- Why Computer Vision?•1 minute
- Related Fields of Computer Vision•5 minutes
- Relevant Fields•1 minute
- Computer Programming & Computer Vision•1 minute
- Computer Vision Awareness•2 minutes
- Timelines & Milestones•8 minutes
- Computer Vision Progression•1 minute
- Computer Vision Applications•9 minutes
- CV Applications•4 minutes
- CV Impact in the Field of Augmented Reality•2 minutes
2 readings•Total 40 minutes
- Resources (Optional): Computer Vision Overview•30 minutes
- Create MATLAB Online Account•10 minutes
4 assignments•Total 95 minutes
- What is Computer Vision?•30 minutes
- Related Fields of Computer Vision•30 minutes
- MATLAB Basics•5 minutes
- MATLAB: Accessing Image Sub-Regions•30 minutes
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
What's included
4 videos1 reading5 assignments
4 videos•Total 32 minutes
- Light Sources•9 minutes
- Pinhole Camera Model•9 minutes
- Digital Camera•6 minutes
- Color Theory•9 minutes
1 reading•Total 30 minutes
- Resources (Optional): Color, Light, & Image Formation•30 minutes
5 assignments•Total 150 minutes
- Light Sources•30 minutes
- Pinhole Camera Model•30 minutes
- Digital Camera•30 minutes
- MATLAB: Color Space•30 minutes
- MATLAB: Color Imaging - RGB Channels•30 minutes
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.
What's included
5 videos1 reading3 assignments
5 videos•Total 32 minutes
- Three-Level Paradigm•8 minutes
- Low-, Mid-, High-Level Vision•2 minutes
- Low-Level Vision•9 minutes
- Mid-Level Vision•7 minutes
- High-Level Vision•7 minutes
1 reading•Total 30 minutes
- Resources (Optional): Low-, Mid- and High-Level Vision•30 minutes
3 assignments•Total 90 minutes
- Three-Level Paradigm•30 minutes
- Low-Level Vision•30 minutes
- MATLAB: Image Gradient Magnitude•30 minutes
In this lecture, we will discuss the Mathematics used in Computer Vision, which includes linear algebra, calculus, probability, and much more.
What's included
8 videos2 readings2 assignments
8 videos•Total 10 minutes
- Mathematic Skills•2 minutes
- Mathematical Preliminaries•0 minutes
- Linear Algebra•2 minutes
- Calculus•1 minute
- Probability Theory•1 minute
- Algorithms•1 minute
- Using Algorithms•2 minutes
- Aligning RGB channels•2 minutes
2 readings•Total 40 minutes
- Resources (Optional): Mathematics for Computer Vision•30 minutes
- Computer Vision Basics - Key Takeaways•10 minutes
2 assignments•Total 32 minutes
- Algorithms•2 minutes
- MATLAB: Aligning RGB Channels•30 minutes
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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 Nov 12, 2022
My Message is going to anyone who demand to up his skill in Digital World, You Ought to Enroll this course..Also if You are a Beginner for Computer Vision world it will Make Like AI
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.
Frequently asked questions
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.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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Financial aid available,