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Columbia University

Features and Boundaries

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.

状态:Computer Graphics
状态:Linear Algebra
初级课程小时

精选评论

TF

5.0评论日期:Jan 20, 2023

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

KJ

5.0评论日期:Apr 27, 2022

Amazing course , Well explained and interesting assignments!!!

GP

5.0评论日期:Dec 20, 2023

Great overview for various topics. The highlight is the simple explanation for the SIFT algorithm operational concept imo.

GS

5.0评论日期:Dec 13, 2021

A​nother excellent course on first principles of comuter vision.

所有审阅

显示:9/9

Marco Morais
5.0
评论日期:Dec 11, 2022
Guy Paiss
5.0
评论日期:Dec 21, 2023
Tony Fu
5.0
评论日期:Jan 21, 2023
Guy Sereff
5.0
评论日期:Dec 14, 2021
Krushi Jethe
5.0
评论日期:Apr 28, 2022
Doris Chen
5.0
评论日期:Aug 28, 2024
Әкім Нұржан Сұлтанұлы
5.0
评论日期:Mar 15, 2024
Joe Serrano
4.0
评论日期:Jan 4, 2023
Nedyalko Prisadnikov
3.0
评论日期:May 29, 2023