About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 12 hours to complete

English

Subtitles: English

What you will learn

  • Check

    Understand what computer vision is and its goals

  • Check

    Identify some of the key application areas of computer vision

  • Check

    Understand the digital imaging process

  • Check

    Apply mathematical techniques to complete computer vision tasks

Skills you will gain

Computer VisionComputer ProgrammingMatlab

Course 1 of 4 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 12 hours to complete

English

Subtitles: English

Learners taking this Course are

  • Machine Learning Engineers
  • Data Scientists
  • Software Engineers
  • Researchers
  • Engineers

Syllabus - What you will learn from this course

Week
1
3 hours to complete

Computer Vision Overview

14 videos (Total 44 min), 2 readings, 4 quizzes
14 videos
Meet Jeff Bier1m
Meet Jungsong Yuan, Ph.D.24s
What is Computer Vision?6m
Why Computer Vision?40s
Related Fields of Computer Vision4m
Relevant Fields56s
Computer Programming & Computer Vision1m
Computer Vision Awareness1m
Timelines & Milestones8m
Computer Vision Progression1m
Computer Vision Applications8m
CV Applications4m
CV Impact in the Field of Augmented Reality1m
2 readings
Resources (Optional): Computer Vision Overview30m
REQUIRED - MATLAB Resources10m
3 practice exercises
What is Computer Vision?2m
Related Fields of Computer Vision2m
MATLAB Basics
Week
2
3 hours to complete

Color, Light, & Image Formation

4 videos (Total 32 min), 1 reading, 5 quizzes
4 videos
Pinhole Camera Model9m
Digital Camera5m
Color Theory8m
1 reading
Resources (Optional): Color, Light, & Image Formation30m
3 practice exercises
Light Sources4m
Pinhole Camera Model2m
Digital Camera2m
Week
3
2 hours to complete

Low-, Mid- & High-Level Vision

5 videos (Total 32 min), 1 reading, 3 quizzes
5 videos
Low-, Mid-, High-Level Vision1m
Low-Level Vision8m
Mid-Level Vision7m
High-Level Vision6m
1 reading
Resources (Optional): Low-, Mid- and High-Level Vision30m
2 practice exercises
Three-Level Paradigm2m
Low-Level Vision2m
Week
4
2 hours to complete

Mathematics for Computer Vision

8 videos (Total 10 min), 2 readings, 2 quizzes
8 videos
Mathematical Preliminaries27s
Linear Algebra1m
Calculus45s
Probability Theory35s
Algorithms38s
Using Algorithms1m
Aligning RGB channels2m
2 readings
Resources (Optional): Mathematics for Computer Vision30m
Computer Vision Basics - Key Takeaways10m
1 practice exercise
Algorithms2m
3.8
47 ReviewsChevron Right

Top reviews from Computer Vision Basics

By AMJun 15th 2019

This course is a good course to start computer vision for beginner level student, and I offer This course to everyone who is eager to learn computer vision conceptually.

By AAMay 6th 2019

The course content is good.There are too many examples and applications.I use python but using MATLAB for the computer vision is new experience for me.

Instructors

Avatar

Radhakrishna Dasari

Instructor
Department of Computer Science
Avatar

Junsong Yuan

Associate Professor and Director of Visual Computing Lab
Computer Science and Engineering

About University at Buffalo

The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs....

About The State University of New York

The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe....

About the Computer Vision Specialization

This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes. The specialization is taught in MATLAB* using computer vision and supporting toolboxes. 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). To learn more, check out a video overview at https://youtu.be/OfxVUSCPXd0. * A free license to install MATLAB for the duration of the course is available from MathWorks....
Computer Vision

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.