Computer Vision Basics
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.
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- Duration 13 hours
- Course by University at Buffalo
-
Offered by
About
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.Modules
What is Computer Vision?
-
4
Videos
-
1
Assignment
1
Assignment
- What is Computer Vision?
4
Videos
- Meet Jeff Bier
- Meet Jungsong Yuan, Ph.D.
- What is Computer Vision?
- Why Computer Vision?
Related Fields of Computer Vision
-
4
Videos
-
1
Assignment
1
Assignment
- Related Fields of Computer Vision
4
Videos
- Related Fields of Computer Vision
- Relevant Fields
- Computer Programming & Computer Vision
- Computer Vision Awareness
Timelines & Milestones
-
2
Videos
2
Videos
- Timelines & Milestones
- Computer Vision Progression
Computer Vision Applications
-
3
Videos
3
Videos
- Computer Vision Applications
- CV Applications
- CV Impact in the Field of Augmented Reality
Computer Vision Overview Resources and Evaluation
-
2
Readings
-
1
ExternalTool
-
1
Plugin
-
1
Assignment
1
Assignment
- MATLAB Basics
1
External Tool
- MATLAB: Accessing Image Sub-Regions
2
Readings
- Resources (Optional): Computer Vision Overview
- REQUIRED - MATLAB Resources
Light Sources
-
1
Videos
-
1
Assignment
1
Assignment
- Light Sources
1
Videos
- Light Sources
Pinhole Camera Model
-
1
Videos
-
1
Assignment
1
Assignment
- Pinhole Camera Model
1
Videos
- Pinhole Camera Model
Digital Camera
-
1
Videos
-
1
Assignment
1
Assignment
- Digital Camera
1
Videos
- Digital Camera
Color Theory
-
1
Videos
-
1
ExternalTool
1
External Tool
- MATLAB: Color Space
1
Videos
- Color Theory
Color, Light, & Image Formation Resources and Evaluation
-
1
Readings
-
1
ExternalTool
1
External Tool
- MATLAB: Color Imaging - RGB Channels
1
Readings
- Resources (Optional): Color, Light, & Image Formation
Three-Level Paradigm
-
2
Videos
-
1
Assignment
1
Assignment
- Three-Level Paradigm
2
Videos
- Three-Level Paradigm
- Low-, Mid-, High-Level Vision
Low-Level Vision
-
1
Videos
-
1
Assignment
1
Assignment
- Low-Level Vision
1
Videos
- Low-Level Vision
Mid-Level Vision
-
1
Videos
1
Videos
- Mid-Level Vision
High-Level Vision
-
1
Videos
1
Videos
- High-Level Vision
Low-, Mid-, & High-Level Vision Resources and Evaluation
-
1
Readings
-
1
ExternalTool
1
External Tool
- MATLAB: Image Gradient Magnitude
1
Readings
- Resources (Optional): Low-, Mid- and High-Level Vision
Mathematical Preliminaries
-
2
Videos
2
Videos
- Mathematic Skills
- Mathematical Preliminaries
Linear Algebra
-
1
Videos
1
Videos
- Linear Algebra
Calculus
-
1
Videos
1
Videos
- Calculus
Probability Theory
-
1
Videos
1
Videos
- Probability Theory
Algorithms
-
2
Videos
-
1
Assignment
1
Assignment
- Algorithms
2
Videos
- Algorithms
- Using Algorithms
Mathematics for Computer Vision Resources and Evaluation
-
1
Videos
-
1
Readings
-
1
ExternalTool
1
External Tool
- MATLAB: Aligning RGB Channels
1
Videos
- Aligning RGB channels
1
Readings
- Resources (Optional): Mathematics for Computer Vision
Computer Vision Basics - Key Takeaways
-
1
Readings
1
Readings
- Computer Vision Basics - Key Takeaways
Auto Summary
"Computer Vision Basics" offered by Coursera is a comprehensive course in the Data Science & AI domain, taught by expert instructors. It delves into making computers see and interpret like humans, covering digital signal processing, neuroscience, and AI. Topics span from color, light, and image formation to various vision levels and essential mathematics. Ideal for curious learners or those seeking a refresher, it requires basic programming skills in MATLAB and foundational knowledge in algebra, calculus, and probability. The 780-minute course includes lectures, demos, hands-on exercises, and project work, available via Starter and Professional subscriptions.
Radhakrishna Dasari
Junsong Yuan