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. Next, we tackle the problem of uncalibrated stereo where the relative positions and orientations of the two cameras are unknown. Interestingly, just from the two images taken by the cameras, we can both determine the relative positions and orientations of the cameras and then use this information to estimate the 3D structure of the scene.
3D Reconstruction - Multiple Viewpoints
This course is part of First Principles of Computer Vision Specialization
Instructor: Shree Nayar
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What you'll learn
Develop a comprehensive model of a camera and learn how to calibrate a camera by estimating its parameters.
Develop a simple stereo system that uses two cameras of known configuration to estimate the 3D structure of a scene.
Design an algorithm for recovering both the structure of the scene and the motion of the camera from a video.
Develop optical flow algorithms for estimating the motion of points in a video sequence.
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There are 5 modules in this course
What's included
7 readings2 discussion prompts8 plugins
What's included
1 reading6 assignments2 discussion prompts5 plugins
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2 readings7 assignments2 discussion prompts7 plugins
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1 reading6 assignments1 discussion prompt6 plugins
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3 readings6 assignments2 discussion prompts6 plugins
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