Computer Vision Basics from Coursera

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.

What's inside

Syllabus

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.

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Develops core concepts and skills for computer vision

Taught by recognized experts, Radhakrishna Dasari and Junsong Yuan

Covers essential elements of computer vision, including digital signal processing, neuroscience, and artificial intelligence

Provides hands-on experience through online labs using MATLAB* and supporting toolboxes

Requires basic programming skills and experience in MATLAB

Assumes familiarity with basic linear algebra, 3D co-ordinate systems and transformations, basic calculus, and basic probability

Reviews summary

Foundational computer vision concepts

According to learners, this course provides a solid introduction to the fundamental concepts of computer vision. Many find the lectures clear and well-explained, particularly appreciating the coverage of mathematics essential for the field. Students highlight the practical value of the hands-on labs and project work, often using MATLAB, which they feel helps solidify understanding. However, some reviewers note that the required mathematical background might be more challenging than anticipated, potentially making it less accessible for those without a strong foundation. While generally positive, a few comments suggest the course could benefit from more in-depth exploration of certain advanced topics or alternative programming environments beyond MATLAB.

Explains necessary math concepts well.

"The explanation of the mathematical concepts used in Computer Vision was very helpful."

"I appreciated the detailed module on the math required; it was crucial for the labs."

"Even though I had the prerequisites, the math review module was a great refresher."

"The course effectively bridges the gap between theory and the math behind it."

Hands-on labs reinforce learning.

"The MATLAB labs are very useful and practical for applying the concepts."

"I really enjoyed the coding exercises; they made the theory click."

"Working on the project using MATLAB was the best part for me, very hands-on."

"The guided labs provided excellent practice and helped solidify understanding."

Excellent introduction to core CV concepts.

"The course provides a very good introduction to the basics of computer vision."

"Excellent foundation for understanding the main concepts and mathematical background."

"Covers the essential topics like image formation, levels of vision, and necessary math."

"I feel I have a solid base to build upon after taking this course."

Could cover some topics deeper.

"Wish there was more depth on specific algorithms or modern CV techniques."

"It's a basic introduction, which is fine, but doesn't go very deep into any single area."

"Good starting point, but expect to need more courses for advanced applications."

Math can be challenging for some.

"While the description mentions basic math, I found some parts quite challenging if you're not already fluent."

"The math prerequisite felt a bit understated; struggled with some of the linear algebra applications."

"Might be tough if your calculus and probability are rusty."

"You really need to have a strong grip on the math before starting, not just basic."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computer Vision Basics with these activities:

Read 'Computer Vision: Algorithms and Applications'

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Gain a comprehensive understanding of computer vision algorithms and applications by reading an authoritative book on the subject.

View Computer Vision on Amazon

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Obtain a copy of the book.
Read the book thoroughly, taking notes and highlighting key concepts.
Complete the exercises and assignments provided in the book.

Review Matrix Vector Operations and Notation

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Revisit matrix vector operations and notation to enhance comprehension of fundamental linear algebra concepts utilized extensively in computer vision.

Browse courses on Linear Algebra

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Review the concepts of matrix and vector algebra.
Practice manipulating matrices and vectors using operations like addition, subtraction, and multiplication.
Familiarize yourself with the notation used to represent matrix vector operations.

Solve Practice Problems on Derivatives and Integration

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Enhance your understanding of calculus by solving practice problems on derivatives and integration, which are essential mathematical concepts for computer vision.

Browse courses on Derivatives

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Review the concepts of derivatives and integration.
Solve a variety of practice problems involving differentiation and integration.
Check your answers and identify areas where you need further practice.

Four other activities

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Show all seven activities

Explore Tutorials on Color Models and Image Processing

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Delve deeper into the fundamentals of computer vision by following guided tutorials that cover topics such as color models and image processing techniques.

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Search for tutorials on color models and image processing.
Follow the tutorials step-by-step, implementing the concepts in your own code.
Experiment with different parameters and techniques to enhance your understanding.

Compile a Glossary of Computer Vision Terminology

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Enhance your understanding of computer vision terminology by creating a comprehensive glossary of key terms and concepts.

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Identify and define key terms related to computer vision.
Organize the terms into categories or a logical structure.
Provide clear and concise definitions for each term.

Answer Questions on Computer Vision Forums

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Reinforce your understanding of computer vision by helping others on forums, clarifying concepts, and sharing your knowledge.

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Identify online forums or discussion groups dedicated to computer vision.
Actively participate in discussions, answering questions and providing insights.
Share your experiences and knowledge to help others.

Build a Simple Image Processing Application

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Solidify your understanding of computer vision concepts by embarking on a project to build a simple image processing application, putting your knowledge into practice.

Browse courses on Image Processing

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Choose a specific image processing task to focus on.
Design and implement an algorithm to perform the task.
Write code to implement your algorithm.
Test and refine your application.
Document your project and share it with others.

Career center

Learners who complete Computer Vision Basics will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

Computer Vision Engineers build and maintain computer vision systems, which are used in a variety of applications, such as self-driving cars and medical imaging. This course would provide a strong foundation for a career in Computer Vision Engineering, as it covers the core concepts of the field and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Computer Vision Engineers, as they often need to use mathematics to solve complex problems.

See salaries and explore the career path for Computer Vision Engineer

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models, which are used to make predictions and decisions based on data. This course would provide a good foundation for a career in Machine Learning Engineering, as it covers the core concepts of machine learning and provides hands-on experience in developing machine learning models. The course's emphasis on computer vision would also be beneficial for Machine Learning Engineers, as many machine learning models are used for computer vision tasks.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use data to solve problems and make predictions. They use a variety of techniques, including machine learning and computer vision. This course would provide a good foundation for a career in Data Science, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Data Scientists, as they often need to use mathematics to solve complex problems.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software applications. They use a variety of programming languages and technologies to create software that meets the needs of users. This course would provide a good foundation for a career in Software Engineering, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Software Engineers, as they often need to use mathematics to solve complex problems.

See salaries and explore the career path for Software Engineer

Robotics Engineer

Robotics Engineers design, build, and maintain robots. They use a variety of technologies, including computer vision, to create robots that can perform a variety of tasks. This course would provide a good foundation for a career in Robotics Engineering, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on 3D co-ordinate systems and transformations would also be beneficial for Robotics Engineers, as they often need to use these concepts to design and build robots.

See salaries and explore the career path for Robotics Engineer

Computer Graphics Engineer

Computer Graphics Engineers design and develop computer graphics systems. They use a variety of techniques, including computer vision, to create computer graphics that are realistic and engaging. This course would provide a good foundation for a career in Computer Graphics Engineering, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on color, light, and image formation would also be beneficial for Computer Graphics Engineers, as they often need to use these concepts to create realistic computer graphics.

See salaries and explore the career path for Computer Graphics Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineers design and develop artificial intelligence systems. They use a variety of techniques, including computer vision, to create artificial intelligence systems that can solve problems and make decisions. This course would provide a good foundation for a career in Artificial Intelligence Engineering, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on deep learning would also be beneficial for Artificial Intelligence Engineers, as deep learning is a key technology used in artificial intelligence systems.

See salaries and explore the career path for Artificial Intelligence Engineer

Computer Vision Researcher

Computer Vision Researchers conduct research in the field of computer vision. They develop new algorithms and techniques for computer vision tasks, such as object recognition and image segmentation. This course would provide a strong foundation for a career in Computer Vision Research, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Computer Vision Researchers, as they often need to use mathematics to develop new algorithms and techniques.

See salaries and explore the career path for Computer Vision Researcher

Data Analyst

Data Analysts use data to solve problems and make decisions. They use a variety of techniques, including machine learning and computer vision, to analyze data and identify trends. This course would provide a good foundation for a career in Data Analysis, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Data Analysts, as they often need to use mathematics to analyze data.

See salaries and explore the career path for Data Analyst

Software Developer

Software Developers design, develop, and maintain software applications. They use a variety of programming languages and technologies to create software that meets the needs of users. This course would provide a good foundation for a career in Software Development, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on mathematical techniques would also be beneficial for Software Developers, as they often need to use mathematics to solve complex problems.

See salaries and explore the career path for Software Developer

Product Manager

Product Managers are responsible for the development and marketing of products. They work with a variety of stakeholders, including engineers, designers, and marketers, to create products that meet the needs of customers. This course would provide a good foundation for a career in Product Management, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on human vision capabilities would also be beneficial for Product Managers, as they need to understand how users interact with products.

See salaries and explore the career path for Product Manager

Technical Writer

Technical Writers create documentation for software and other technical products. They use a variety of writing styles and techniques to create documentation that is clear and concise. This course would provide a good foundation for a career in Technical Writing, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on writing and communication would also be beneficial for Technical Writers, as they need to be able to communicate complex technical information in a clear and concise manner.

See salaries and explore the career path for Technical Writer

Systems Analyst

Systems Analysts design and develop computer systems. They work with a variety of stakeholders, including users, engineers, and managers, to create systems that meet the needs of organizations. This course would provide a good foundation for a career in Systems Analysis, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on systems design and development would also be beneficial for Systems Analysts, as they need to be able to design and develop complex systems.

See salaries and explore the career path for Systems Analyst

Quality Assurance Analyst

Quality Assurance Analysts test and evaluate software and other technical products to ensure that they meet quality standards. They use a variety of testing techniques to identify and fix defects. This course would provide a good foundation for a career in Quality Assurance, as it covers the core concepts of computer vision and provides hands-on experience in developing computer vision programs. The course's emphasis on testing and evaluation would also be beneficial for Quality Assurance Analysts, as they need to be able to identify and fix defects in software and other technical products.

See salaries and explore the career path for Quality Assurance Analyst