John Hopkins University - Computer Vision Basics
- Offered byCoursera
Computer Vision Basics at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Computer Vision Basics at Coursera Highlights
- 43% got a tangible career benefit from this course.
- 25% got a pay increase or promotion.
- Earn a shareable certificate upon completion.
Computer Vision Basics at Coursera Course details
- 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.
Computer Vision Basics at Coursera Curriculum
Computer Vision Overview
Meet Jeff Bier
Meet Jungsong Yuan, Ph.D.
What is Computer Vision?
Why Computer Vision?
Related Fields of Computer Vision
Relevant Fields
Computer Programming & Computer Vision
Computer Vision Awareness
Timelines & Milestones
Computer Vision Progression
Computer Vision Applications
CV Applications
CV Impact in the Field of Augmented Reality
Resources (Optional): Computer Vision Overview
REQUIRED - MATLAB Resources
What is Computer Vision?
Related Fields of Computer Vision
MATLAB Basics
Color, Light, & Image Formation
Light Sources
Pinhole Camera Model
Digital Camera
Color Theory
Resources (Optional): Color, Light, & Image Formation
Light Sources
Pinhole Camera Model
Digital Camera
Low-, Mid- & High-Level Vision
Three-Level Paradigm
Low-, Mid-, High-Level Vision
Low-Level Vision
Mid-Level Vision
High-Level Vision
Resources (Optional): Low-, Mid- and High-Level Vision
Three-Level Paradigm
Low-Level Vision
Mathematics for Computer Vision
Mathematic Skills
Mathematical Preliminaries
Linear Algebra
Calculus
Probability Theory
Algorithms
Using Algorithms
Aligning RGB channels
Resources (Optional): Mathematics for Computer Vision
Computer Vision Basics - Key Takeaways
Algorithms
Computer Vision Basics at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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