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Features and Boundaries(으)로 돌아가기

컬럼비아대학교의 Features and Boundaries 학습자 리뷰 및 피드백

5.0
별점
12개의 평가

강좌 소개

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....

최상위 리뷰

GS

2021년 12월 13일

Another excellent course on first principles of comuter vision.

JK

2022년 4월 27일

Amazing course , Well explained and interesting assignments!!!

필터링 기준:

Features and Boundaries의 2개 리뷰 중 1~2

교육 기관: Guy S

2021년 12월 14일

교육 기관: Krushi J

2022년 4월 28일