Chevron Left
Back to Features and Boundaries

Learner Reviews & Feedback for Features and Boundaries by Columbia University

12 ratings

About the Course

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....

Top reviews


Dec 13, 2021

Another excellent course on first principles of comuter vision.


Apr 27, 2022

Amazing course , Well explained and interesting assignments!!!

Filter by:

1 - 2 of 2 Reviews for Features and Boundaries

By Guy S

Dec 14, 2021

By Krushi J

Apr 28, 2022