Reconstruction and Analysis of 3D Scenes (FSI-SR0)

Academic year 2020/2021
Supervisor: Mgr. Jana Procházková, Ph.D.  
Supervising institute: ÚM all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
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.
Learning outcomes and competences:
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).
Prerequisites:
elementary knowledge of mathematical analysis and algebra (matrix, derivative), computer graphics, the recommended is the knowledge of programming language (C, C++, Pascal, atd) or programm (e.g. Matlab).
Course contents:
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, geography and autonomous traffic 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. We will also work with 3D printer Voxelizer.
We will use Arduino Engineering Kit for testing of proposed algorithms.
Students prepare their own implementation of some of the algorithm in the last lectures of semester.
Teaching methods and criteria:
The lectures are the based on the presentation and programming of the point cloud processing methods. Two lectures will be in laboratory on the optical scanner ATOS (calibration and 3D scanning). In the end of the semester students will work on the computer on their preferable research topic.
Assesment methods and criteria linked to learning outcomes:
Students will prepare the project and present the project on the end of the semester.
Controlled participation in lessons:
The lecture attendance is compulsory.
Type of course unit:
    Lecture  13 × 1 hrs. optionally                  
    Computer-assisted exercise  13 × 2 hrs. compulsory                  
Course curriculum:
    Lecture 1st week: The data acquisition (Terrain, Mobile, Airborne) in dependance of the application. Passive (Structure from Motion) and active methods (Time of Flight, laser)
2nd week: Point cloud registration (methods PCA, SVD, ICP).
3rd week: RANSAC - algorithm and its usage, feature extraction
4-5th week: Laboratory measurements on the optical scanner ATOS and hand scanners.
6th week: Point cloud processing in software (GOM Inspect, Rhinoceros, etc.)
7th week: 3D printing - principles, settings, problems.
8th week: Arduino Engineering Kit - vehicle Rover can navigate between given reference points, move objects with a forklift.
9-12th week: Consultations
13th week: Presentation of the seminar work.
    Computer-assisted exercise 1st week: The data acquisition (Terrain, Mobile, Airborne) in dependance of the application, Matlab programming.
2nd week: Point cloud registration - MATLAB or other programming languages.
3rd week: RANSAC programming.
4-5th Laboratory measurements on the optical scanner ATOS and using hand scanners.
6th week: Point cloud processing in software (GOM Inspect, Voxelizer, Rhinoceros). Creating own models for 3D printing.
7th week: 3D printing of models (Voxelizer 3D printer)
8th week: Arduino Engineering Kit - vehicle rover programming.
9-12th week: Seminar work with consultations.
13th week: Presentation of the seminar work.
Literature - fundamental:
1. WEINMANN, Martin. Reconstruction and Analysis of 3D Scenes. Switzerland: Springer, 2016.
2. HUGHES, John F. Computer graphics: principles and practice. Third edition. ISBN 978-0-321-39952-6.
3. SHIRLEY, Peter. Fundamentals of Computer Graphics. 2nd ed. Welesley: A K Peters, c2005. ISBN 1-56881-269-8.
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
M2A-P full-time study M-MAI Mathematical Engineering -- GCr 4 Compulsory-optional 2 1 S