Course detail
Reconstruction and Analysis of 3D Scenes
FSI-QRA Acad. year: 2024/2025 Winter semester
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
Supervisor
Department
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).
The study programmes with the given course
Programme N-AAE-P: Advanced Automotiv Engineering, Master's, compulsory-optional
Programme C-AKR-P: , Lifelong learning
specialization CZS: , elective
Type of course unit
Lecture
26 hours, optionally
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 hours, compulsory
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