Photogrammetry and 3D Computer Vision

Photogrammetry and 3D computer vision aim at recovering the structure of real-world objects/scenes from images. This course is about the theories, methodologies, and techniques of 3D computer vision for the built environment. In the term of this course, students will learn the basic knowledge and algorithms in 3D computer vision through a series of lectures, reading materials, lab exercises, and group assignments. The topics cover the whole pipeline of reconstructing 3D models from images:

- Cameras models: how 3D points from the real world get projected onto the image plane and how to recover the camera parameters from a set of observations;

- Epipolar geometry: the geometric relations between corresponding image points;

- Image matching: define and match image features to establish correspondences between images;

- Structure from motion: recover/refine geometry and camera parameters from a set of images;

- Multi-view stereo for recovering dense geometry (e.g., point clouds) from images;

- Surface reconstruction: obtain 3D surface models of real-world objects from point clouds.