Introduction to Computer Vision
In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most...
By Amanda Wang on Coursera
About This Course
In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most common algorithms for feature detection, extraction, and matching to align satellite images and stitch images together to create a single image of a larger scene. Features are used in applications like motion estimation, object tracking, and machine learning. You’ll use features to estimate geometric transformations between images and perform image registration. Registration is important whenever you need to compare images of the same scene taken at different times or combine images acquired from different scientific instruments, as is common with hyperspectral and medical images. You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your computer vision tasks. You will be provided free access to MATLAB for the course duration to complete your work. To be successful in this course, it will help to have some prior image processing experience. If you are new to image data, it’s recommended to first complete the Image Processing for Engineering and Science specialization.
Topics Covered
Frequently Asked Questions
How much does Introduction to Computer Vision cost?
Visit the Introduction to Computer Vision course page for current pricing and available discounts.
Who teaches Introduction to Computer Vision?
Introduction to Computer Vision is taught by Amanda Wang, MathWorks.
What skill level is Introduction to Computer Vision for?
This course is designed for beginner learners.
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