3D Scanning

HrvatskihrEnglishen

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3D Scanning

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

list technologies which are used in 3D scanning
compare 3D scanning technologies and select the best one depending on the application
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

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