This course is part of the First Principles of Computer Vision Specialization

4.9
stars
20 ratings

Shree Nayar

2,147 already enrolled

Offered By

First Principles of Computer Vision SpecializationColumbia University

About this Course

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This course focuses on the detection of features and boundaries in images. Feature and boundary detection is a critical preprocessing step for a variety of vision tasks including object detection, object recognition and metrology – the measurement of the physical dimensions and other properties of objects. The course presents a variety of methods for detecting features and boundaries and shows how features extracted from an image can be used to solve important vision tasks.
We begin with the detection of simple but important features such as edges and corners. We show that such features can be reliably detected using operators that are based on the first and second derivatives of images. Next, we explore the concept of an “interest point” – a unique and hence useful local appearance in an image. We describe how interest points can be robustly detected using the SIFT detector. Using this detector, we describe an end-to-end solution to the problem of stitching overlapping images of a scene to obtain a wide-angle panorama. Finally, we describe the important problem of finding faces in images and show several applications of face detection.

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Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 5 in the

First Principles of Computer Vision Specialization

Beginner Level

Students should know the fundamentals of linear algebra and calculus. The knowledge of any programming language is beneficial, though not required.

Approx. 22 hours to complete

English

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What you will learn

Learn how to detect edges and corners in images.
Develop active contours (snakes) to find complex object boundaries.
Learn about the Hough Transform for finding simple parametric shapes in images.
Learn about image transformations and how to estimate the homography between two images.

Skills you will gain

Scale Space
Active Contours
Image Transformations
Edge and Corner Detection
SIFT Detector

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 2 of 5 in the

First Principles of Computer Vision Specialization

Beginner Level

Students should know the fundamentals of linear algebra and calculus. The knowledge of any programming language is beneficial, though not required.

Approx. 22 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

5/5 (6 Ratings)

Shree Nayar

T. C. Chang Professor

Computer Science

9,177 Learners

5 Courses

Offered by

Columbia University

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Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Getting Started: Features and Boundaries

2 hours to complete

7 readings

Week2

Week 2

4 hours to complete

Edge Detection

4 hours to complete

1 reading

Week3

Week 3

4 hours to complete

Boundary Detection

4 hours to complete

1 reading

Week4

Week 4

4 hours to complete

SIFT Detector

4 hours to complete

1 reading

Reviews

4.9

5 reviews

5 stars
90%
4 stars
10%

TOP REVIEWS FROM FEATURES AND BOUNDARIES

by GSDec 13, 2021

Another excellent course on first principles of comuter vision.

by JKApr 27, 2022

Amazing course , Well explained and interesting assignments!!!

by TFJan 20, 2023

A little bit advanced, but the quality of the slides and presentations is superb.

View all reviews

About the First Principles of Computer Vision Specialization

This specialization presents the first comprehensive treatment of the foundations of computer vision. It focuses on the mathematical and physical underpinnings of vision and has been designed for learners, practitioners and researchers who have little or no knowledge of computer vision. The program includes a series of 5 courses. Any learner who completes this specialization has the potential to build a successful career in computer vision, a thriving field that is expected to increase in importance in the coming decades.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Features and Boundaries

About this Course

What you will learn

Skills you will gain