Popis predmeta

Course Description

Introduction to 3D scanning and profilometry. Image formation model. Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic camera parameters. Single camera calibration. Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix. Calibration of a stereo camera pair. Triangulation and 3D reconstruction. Correspondence problem. Keypoints and RANSAC. Homographies. Three views. Trifocal tensor. Geometries with more than three views. Bundle adjustment. Autocalibration. Cheirality. Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Types of projectors. Projector calibration. Fringe projection profilometry. Phase unwrapping. Systems using multiple cameras and projectors. Time-of-flight cameras. Coding functions. Laser 3D scanning. Point clouds. Registration. ICP algorithm. Handheld 3D scanners.

Learning Outcomes

  1. list technologies which are used in 3D scanning
  2. compare 3D scanning technologies and select the best one depending on the application
  3. analyze accuracy and uncertainty of 3D reconstruction

Forms of Teaching

Lectures

Lectures present theoretical concepts.

Seminars and workshops

Seminar includes discussion on theoretical concepts presented during lectures.

Laboratory

Laboratory 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 % 15 % 50 % 15 %
Seminar/Project 50 % 15 % 50 % 15 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 35 %
Exam: Written 50 % 70 %
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

  1. Introduction to 3D scanning and profilometry. Image formation model.
  2. Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic parameters.
  3. Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix.
  4. Triangulation and 3D reconstruction. Correspondence problem. Keypoints. RANSAC. Homographies.
  5. Single camera calibration. Calibration of a stereo camera pair. Autocalibration.
  6. Three views. Trifocal tensor. Geometries with more than three views.
  7. Bundle adjustment. Cheirality.
  8. Midterm exam
  9. Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Light sources and projectors.
  10. Fringe projection profilometry. Phase unwrapping.
  11. Projector calibration. Systems using multiple cameras and projectors.
  12. Time-of-flight cameras. Coding functions.
  13. Point clouds. Registration. ICP algorithm.
  14. Laser 3D scanning. Handheld 3D scanners. Other 3D scanning methods.
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Elective Courses of the Profile (1. semester) Elective Coursesof the Profile (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) (3. semester)

Literature

Richard Hartley, Andrew Zisserman (2004.), Multiple View Geometry in Computer Vision, Cambridge University Press
Pietro Zanuttigh, Giulio Marin, Carlo Dal Mutto, Fabio Dominio, Ludovico Minto, Guido Maria Cortelazzo (2016.), Time-of-Flight and Structured Light Depth Cameras, Springer
Silvio Giancola, Matteo Valenti, Remo Sala (2018.), A Survey on 3D Cameras: Metrological Comparison of Time-of-Flight, Structured-Light and Active Stereoscopy Technologies, Springer

For students

General

ID 222434
  Winter semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
5 Seminar
15 Laboratory exercises

Grading System

87 Excellent
75 Very Good
64 Good
51 Acceptable

Similar Courses

Learning Outcomes

  1. list technologies which are used in 3D scanning
  2. compare 3D scanning technologies and select the best one depending on the application
  3. analyze accuracy and uncertainty of 3D reconstruction

Forms of Teaching

Lectures

Lectures present theoretical concepts.

Seminars and workshops

Seminar includes discussion on theoretical concepts presented during lectures.

Laboratory

Laboratory 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 % 15 % 50 % 15 %
Seminar/Project 50 % 15 % 50 % 15 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 35 %
Exam: Written 50 % 70 %
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

  1. Introduction to 3D scanning and profilometry. Image formation model.
  2. Perspective projection. Decomposition of the perspective projection matrix. Intrinsic and extrinsic parameters.
  3. Binocular vision. Stereo camera pair. Epipolar constraint. Stereo rectification. Fundamental matrix.
  4. Triangulation and 3D reconstruction. Correspondence problem. Keypoints. RANSAC. Homographies.
  5. Single camera calibration. Calibration of a stereo camera pair. Autocalibration.
  6. Three views. Trifocal tensor. Geometries with more than three views.
  7. Bundle adjustment. Cheirality.
  8. Midterm exam
  9. Structured light. Classification of structured light patterns. One-shot and multiple-shot patterns. Light sources and projectors.
  10. Fringe projection profilometry. Phase unwrapping.
  11. Projector calibration. Systems using multiple cameras and projectors.
  12. Time-of-flight cameras. Coding functions.
  13. Point clouds. Registration. ICP algorithm.
  14. Laser 3D scanning. Handheld 3D scanners. Other 3D scanning methods.
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Elective Courses of the Profile (1. semester) Elective Coursesof the Profile (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) (3. semester)

Literature

Richard Hartley, Andrew Zisserman (2004.), Multiple View Geometry in Computer Vision, Cambridge University Press
Pietro Zanuttigh, Giulio Marin, Carlo Dal Mutto, Fabio Dominio, Ludovico Minto, Guido Maria Cortelazzo (2016.), Time-of-Flight and Structured Light Depth Cameras, Springer
Silvio Giancola, Matteo Valenti, Remo Sala (2018.), A Survey on 3D Cameras: Metrological Comparison of Time-of-Flight, Structured-Light and Active Stereoscopy Technologies, Springer

For students

General

ID 222434
  Winter semester
5 ECTS
L0 English Level
L1 e-Learning
30 Lectures
5 Seminar
15 Laboratory exercises

Grading System

87 Excellent
75 Very Good
64 Good
51 Acceptable

Similar Courses