3D Scanning
Data is displayed for the academic year: 2024./2025.
Lecturers
Course Description
In this course students gain knowledge about 3D scanning.
The following topics are covered: Introduction to 3D scanning and profilometry. Image formation model. Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic parameters. Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix. Triangulation and 3D reconstruction. Correspondence problem. Keypoints. RANSAC. Homographies. Single camera calibration. Calibration of a stereo camera pair. Autocalibration. Three views. Trifocal tensor. Geometries with more than three views. Bundle adjustment. Cheirality. Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Light sources and projectors. Fringe projection profilometry. Phase unwrapping. Projector calibration. Systems using multiple cameras and projectors. Time-of-flight cameras. Coding functions. Point clouds. Registration. ICP algorithm. Laser 3D scanning. Handheld 3D scanners.
The following topics are covered: Introduction to 3D scanning and profilometry. Image formation model. Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic parameters. Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix. Triangulation and 3D reconstruction. Correspondence problem. Keypoints. RANSAC. Homographies. Single camera calibration. Calibration of a stereo camera pair. Autocalibration. Three views. Trifocal tensor. Geometries with more than three views. Bundle adjustment. Cheirality. Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Light sources and projectors. Fringe projection profilometry. Phase unwrapping. Projector calibration. Systems using multiple cameras and projectors. Time-of-flight cameras. Coding functions. Point clouds. Registration. ICP algorithm. Laser 3D scanning. Handheld 3D scanners.
Prerequisites
A good background in mathematics including linear algebra, calculus and geometry.
Study Programmes
University graduate
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Learning Outcomes
- List technologies which are used in 3D scanning
- Explain the image formation model and perspective projection
- Explain and perform camera calibration
- Compare 3D scanning methods
- Analyze accuracy and uncertainty of 3D reconstruction
- Select 3D scanning method depending on the application
Forms of Teaching
Lectures
Lectures present theoretical concepts.
Seminars and workshopsSeminar includes discussion on theoretical concepts presented during lectures.
LaboratoryLaboratory exercises facilitate better understanding of the problems of 3D scanning.
Grading Method
Continuous Assessment | Exam | |||||
---|---|---|---|---|---|---|
Type | Threshold | Percent of Grade | Threshold | Percent of Grade | ||
Laboratory Exercises | 50 % | 20 % | 50 % | 20 % | ||
Seminar/Project | 50 % | 20 % | 50 % | 20 % | ||
Mid Term Exam: Written | 0 % | 30 % | 0 % | |||
Final Exam: Written | 0 % | 30 % | ||||
Exam: Written | 50 % | 60 % |
Comment:
The mandatory prerequisites for the passing grade are at least 50% points achieved on the midterm and on the final exam combined, and at least 50% on the laboratory and on the seminar.
Week by Week Schedule
- Introduction to 3D scanning and profilometry. Image formation model.
- Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic parameters.
- Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix.
- Triangulation and 3D reconstruction. Correspondence problem. Keypoints. RANSAC. Homographies.
- Single camera calibration. Calibration of a stereo camera pair. Autocalibration.
- Three views. Trifocal tensor. Geometries with more than three views.
- Bundle adjustment. Cheirality.
- Midterm exam
- Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Light sources and projectors.
- Fringe projection profilometry. Phase unwrapping.
- Projector calibration. Systems using multiple cameras and projectors.
- Time-of-flight cameras. Coding functions.
- Point clouds. Registration. ICP algorithm.
- Laser 3D scanning. Handheld 3D scanners. Other 3D scanning methods.
- Final exam
Literature
General
ID 222434
Winter semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
5 Seminar
0 Exercises
15 Laboratory exercises
0 Project laboratory
0 Physical education excercises
Grading System
87 Excellent
75 Very Good
64 Good
51 Sufficient