3D Reconstruction - Single Viewpoint (Coursera)

Offered by Columbia University,
3D Reconstruction - Single Viewpoint (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.

What You Will Learn

  • Learn radiometric concepts related to light and how it interacts with scenes.
  • Understand reflectance models and the different physical mechanisms that determine the appearance of a surface.
  • Develop a method for recovering the shape of a surface from its shading.
  • Understand the principle of photometric stereo where a dense surface normal map of the scene is obtained by varying the illumination direction.

Course 3 of 5 in the First Principles of Computer Vision Specialization

Syllabus

WEEK 1: Getting Started: 3D Reconstruction - Single Viewpoint
WEEK 2: Radiometry and Reflectance
WEEK 3: Photometric Stereo
WEEK 4: Shape from Shading
WEEK 5: Depth from Defocus
WEEK 6: Active Illumination Methods

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

The Civil War and Reconstruction - 1850-1861: A House Divided (edX) EdX
Columbia University,ColumbiaX

The Civil War and Reconstruction - 1850-1861: A House Divided (edX)

Discover how the issue of slavery came to dominate American politics, and how political leaders struggled and failed to resolve the growing crisis in the nation. A House Divided: The Road to Civil War, 1850-1861 begins by examining how generations of historians have explained the crisis of the Union. After discussing the institution of slavery and its central role in the southern and national economies, it turns to an account of the political and social history of the 1850s.

Self Paced
Self-Paced
Voyage au cœur du vivant avec les rayons X : la cristallographie (FUN) FUN
Université Paris-Saclay

Voyage au cœur du vivant avec les rayons X : la cristallographie (FUN)

L’utilisation des structures tridimensionnelles de macromolécules biologiques fait partie du quotidien d’un grand nombre de biologistes. Ces structures permettent de comprendre leur fonctionnement, de dessiner des mutants pour étudier leur fonction, de dessiner des molécules pour les bloquer ou les activer. L’approche majeure pour résoudre la structure tridimensionnelle de macromolécules biologiques est la cristallographie aux rayons X. Ce MOOC est une initiation complète à la cristallographie biologique : depuis l'histoire de la méthode jusqu'à ses outils concrets.Nous vous transmettons nos connaissances et notre expérience par le biais de vidéos théoriques et en situation.

No sessions available
5-12 Weeks
Introduction to American History: From Reconstruction to World War, 1865-1919 (FutureLearn) FutureLearn
The University of Newcastle, Australia

Introduction to American History: From Reconstruction to World War, 1865-1919 (FutureLearn)

Explore American history since 1865. Learn about the Civil War, Reconstruction, segregation and US foreign policy. Discover key moments in American history after the Civil War. American history is vast and complex. Through this course you will explore some of its key moments - examining domestic history and foreign relations.

No sessions available
3 Weeks
3D Reconstruction - Multiple Viewpoints (Coursera) Coursera
Columbia University

3D Reconstruction - Multiple Viewpoints (Coursera)

This course focuses on the recovery of the 3D structure of a scene from images taken from different viewpoints. We start by first building a comprehensive geometric model of a camera and then develop a method for finding (calibrating) the internal and external parameters of the camera model. Then, we show how two such calibrated cameras, whose relative positions and orientations are known, can be used to recover the 3D structure of the scene. This is what we refer to as simple binocular stereo.

Sep 21st 2026
5-12 Weeks
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Oct 12th 2026
4 Weeks
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Oct 12th 2026
4 Weeks
Probabilistic Graphical Models 2: Inference (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more.

Oct 12th 2026
5-12 Weeks