About

Photogrammetry and 3D Computer Vision (3DV) 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, you will learn the basic knowledge and algorithms in 3D computer vision through a series of lectures, reading materials, lab exercises, and group assignments.

Contents

The topics of this course cover the whole pipeline of reconstructing 3D models from images:

Goals

After finishing this course, you will have gained knowledge of 3D computer vision techniques and the skills to apply them for recovering 3D geometry of real-world objects from images. Specifically, you will be able to:

Assessment

The assessment of this course consists of three group assignments and the final written exam. The final grade is based on the evaluation of both the assignments and the final exam, breaking down into:

Pass or fail? Grading is done on a 10-point scale, and the final marks are rounded off to the nearest full and half figures. To pass the course, all assignments and the final exam must be graded greater or equal to 5.5, and a total of 5.75 or above is required to pass the course.

Repair and retake options. Any component of the assessment graded 5.5 or lower is eligible for one more opportunity to retake (for the exam) or repair (for assignments). A repair is a revision or addition to an existing assignment, and a successful repair will only be assessed with a 6.0. A retake is an entirely new examination.

Prerequisites

Course logistics

Lecturers and teaching assistant

Liangliang Liangliang
Liangliang Nan Nail Ibrahimli
LiangliangNan#0976 nibrahimli#5857

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