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學生對 哥伦比亚大学 提供的 Features and Boundaries 的評價和反饋

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10 個評分
2 條評論

課程概述

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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GS

2021年12月13日

Another excellent course on first principles of comuter vision.

JK

2022年4月27日

Amazing course , Well explained and interesting assignments!!!

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1 - Features and Boundaries 的 2 個評論(共 2 個)

創建者 Guy S

2021年12月14日

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

創建者 JETHE K

2022年4月28日

Amazing course , Well explained and interesting assignments!!!