Course detail

Reconstruction and Analysis of 3D Scenes

FSI-QRAAcad. year: 2024/2025

The subject concerns the reconstruction and analysis of 3D scenes that are based on point clouds. This research area is important in the reverse engineering, robotics and autonomous systems. First part of the lectures deals with the data acquisition types and algorithms as registration, edge detection, feature extraction. In laboratory we make the measurement with optical scanner ATOS and other hand scanners. We will process the point cloud with software GOM inspect and Rhinoceros. 
 Arduino Engineering Kit will be used for rover control.
Students prepare their own implementation of some of the algorithm in the last lectures of semester.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

Mgr. Jana Procházková, Ph.D.

Department

Institute of Mathematics (ÚM)

Entry knowledge

elementary knowledge of mathematical analysis and algebra (matrix, derivative), computer graphics, the recommended is the knowledge of programming language (C, C++, Pascal, atd) and programm (e.g. Matlab).

Rules for evaluation and completion of the course

Students will prepare the project and present the project on the end of the semester. The students can answer the questions due to their topic. The evaluation is given by this presentation and question answering. 


The lecture attendance is compulsory.

Aims

The main gist of the subject is to understand the point cloud and its processing algorithms. The practical part will show the 3D scanning and 3D printing technology and the 3D scene algorithms.
Students will learn about the point clouds, its acquisition (3D scanning), usage (3D printing, Arduino scene analysis) and post-processing (edge or object detection, registration).

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

HUGHES, John F. Computer graphics: principles and practice. Third edition. ISBN 978-0-321-39952-6. (EN)
LIU, Shan, Min ZHANG, Pranav KADAN a Jay KUO. 3D Point Cloud Analysis. NY, USA: Springer, 2021. ISBN 978-3-030-89179-4. (EN)
Introduction to Pointcloudmetry: Point Clouds from Laser Scanning and Photogrammetry. UK: Whittles Publishing, 2023. ISBN 1849954798. (EN)
WEINMANN, Martin. Reconstruction and Analysis of 3D Scenes. Switzerland: Springer, 2016.

Recommended reading

Introduction to Pointcloudmetry: Point Clouds from Laser Scanning and Photogrammetry. UK: Whittles Publishing, 2023. ISBN 1849954798. (EN)
LIU, Shan, Min ZHANG, Pranav KADAN a Jay KUO. 3D Point Cloud Analysis. NY, USA: Springer, 2021. ISBN 978-3-030-89179-4. (EN)
WEINMANN, Martin. Reconstruction and Analysis of 3D Scenes. Switzerland: Springer, 2016. (EN)

Classification of course in study plans

  • Programme N-AAE-P Master's 1 year of study, winter semester, compulsory-optional

  • Programme C-AKR-P Lifelong learning

    specialization CZS , 1 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Mgr. Jana Procházková, Ph.D.

Syllabus

Lectures:
1.The data acquisition (Terrain, Mobile, Airborne) in dependance of the application. Passive (Structure from Motion) and active methods (Time of Flight, laser)
2. RANSAC - algorithm and its usage, feature extraction
3.-4. Point cloud registration (methods PCA, SVD, ICP, FPFH)
5. Ground point detection, clustering
6. Comparison spatial methods with image analysis methods
7. Laboratory measurements on the optical scanner ATOS and hand scanners
8. Point cloud processing in software (GOM Inspect, Rhinoceros, etc.), work with real scanned data
9. 3D printing - principles, settings, problems
10. Arduino Engineering Kit - vehicle Rover can navigate between given reference points, move objects with a forklift
11.-12. Consultations
13. Presentation of the seminar work

Computer-assisted exercise

26 hod., compulsory

Teacher / Lecturer

Mgr. Jana Procházková, Ph.D.

Syllabus

Exercise (with computers):

1. Data capture methods (Terrain, Mobile, Airborne) and their use, SFM Matlab programming, data capture using Intel Real Sense, IPad Pro
2. RANSAC - line, plane, testing
3. -4.: Programming registration methods using predefined functions, influence of parameters on results
5. Land point detection, clustering
6. Image processing methods and their comparison with methods used for 3D (derivative, edge detectors, etc.)
7. Scanning in the laboratory - ATOS
8. Practical exercises with acquired data
9. 3D printing - model design in Rhinoceros, printing
10. Arduino Engineering Kit - programming the Rover and its orientation in space and functions, simple circuit design with Arduino
11. -12. Semester project consultation
13. Presentation of final projects