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Learner Reviews & Feedback for 3D Reconstruction - Single Viewpoint by Columbia University

4.9
stars
36 ratings

About the Course

This course focuses on the recovery of the 3D structure of a scene from its 2D images. In particular, we are interested in the 3D reconstruction of a rigid scene from images taken by a stationary camera (same viewpoint). This problem is interesting as we want the multiple images of the scene to capture complementary information despite the fact that the scene is rigid and the camera is fixed. To this end, we explore several ways of capturing images where each image provides additional information about the scene. In order to estimate scene properties (depth, surface orientation, material properties, etc.) we first define several important radiometric concepts, such as, light source intensity, surface illumination, surface brightness, image brightness and surface reflectance. Then, we tackle the challenging problem of shape from shading - recovering the shape of a surface from its shading in a single image. Next, we show that if multiple images of a scene of known reflectance are taken while changing the illumination direction, the surface normal at each scene point can be computed. This method, called photometric stereo, provides a dense surface normal map that can be integrated to obtain surface shape. Next, we discuss depth from defocus, which uses the limited depth of field of the camera to estimate scene structure. From a small number of images taken by changing the focus setting of the lens, a dense depth of the scene is recovered. Finally, we present a suite of techniques that use active illumination (the projection of light patterns onto the scene) to get precise 3D reconstructions of the scene. These active illumination methods are the workhorse of factory automation. They are used on manufacturing lines to assemble products and inspect their visual quality. They are also extensively used in other domains such as driverless cars, robotics, surveillance, medical imaging and special effects in movies....

Top reviews

CF

Jan 31, 2022

Excellent theoretical course, great content and the teacher explains very well. This course would be great with a complement of labs or small code practices.

MM

Dec 28, 2022

Professor Nayar is an amazing teacher and the lectures are pure gold. FPCV is a great introduction to computer vision.

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1 - 8 of 8 Reviews for 3D Reconstruction - Single Viewpoint

By Venkat k

鈥�

Mar 27, 2023

Very a great theoretical course! beginners to best understand of cv

By Christian J R F

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Feb 1, 2022

Excellent theoretical course, great content and the teacher explains very well. This course would be great with a complement of labs or small code practices.

By Marco M

鈥�

Dec 28, 2022

Professor Nayar is an amazing teacher and the lectures are pure gold. FPCV is a great introduction to computer vision.

By Alex Y

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Sep 10, 2023

Interesting material popular explained. Good as entry point into the Computer Vision world

By Krushi J

鈥�

Apr 29, 2022

Amazing course , Well explained and interesting assignments!!!

By Munadi S

鈥�

Jan 16, 2024

Learnt lots of interesting concepts

By 袦械褉褍械褉褌 袣

鈥�

Apr 26, 2024

goooooooooooooooooooooooooood

By 袞邪薪褋械褉褨泻 袦 覛

鈥�

Apr 20, 2024

泻谢邪褋褋薪芯