Duration
10h Th, 15h Pr, 40h Proj.
Number of credits
| Master in geography: geomatics (120 ECTS) | 5 crédits | |||
| Master in geography : geomatics and surveying (120 ECTS) | 5 crédits |
Lecturer
N...
Substitute(s)
Language(s) of instruction
French language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The "Immersive 3D Environment" course will allow you to develop an expertise around 3D semantic integration and the creation of immersive environments. Your objective is to complete the course by carrying out the established project.
To help you realize this project, I provide you with 3 tools:
- Theoretical resources, to prepare you and enable you to rely on a clear support
- Practical work, to directly implement the solution envisioned
- A supervised support to help and guide you through the project
- 3D point cloud processing
- 3D mesh processing
- Registration and pre-processing
- Semi-automatic and/or automatic point cloud segmentation
- Implementation of a point cloud classification method
- Establishing a complete classification of a dataset
- Integration in a virtual environment of your choice (Virtual tour, Virtual Reality, Augmented Reality, Mixed Reality, 3D Web Platform...)
Learning outcomes of the learning unit
Develop an artificial intelligence for the detection and classification of 3D point clouds (and data). In addition, you will be able to integrate these datasets in an immersive environment (e. g. virtual, augmented, mixed reality...)
Prerequisite knowledge and skills
- 3D Acquisition (GEOG0063) + prerequisite
- 3D Recognition & Understanding (GEOG0064) + prerequisite
- Computer Sciences basics & code
Planned learning activities and teaching methods
The training process is relatively simple but not necessarily intuitive if you are used to traditional training.
You will not take courses that lead to exams with quotations.
You will carry out missions that lead to reports, calculations and/or support to validate the acquisition of skills.
In other words, to do this training I ask you to acquire all the essential skills of a professional.
The projects are reconstructions of professional scenarios, simulations of the daily life of a professional, if you prefer. In the project, I give you a list of deliverables or tasks to be carried out in compliance with requirements. Then it's up to you. As in real life, these activities can take several weeks (or even months).
The idea of project-based pedagogy is to enable you to learn under conditions that are as realistic as possible. So the projects push you to:
Contextualize your practices
Plan your work in the short/medium/long term
Find the information you need to solve a problem
Create quality deliverables that you can use during interviews
Present your work publicly
Improve yourself with resources and feedback
The logistical and scheduling organization can be variable, but a certain amount of theory will be provided before each mission is carried out. The missions will partly and/or fully be realized in pratical sessions
Mode of delivery (face-to-face ; distance-learning)
It is a face-to-face teaching. The theoretical and practical sessions in controlled autonomy take place on the day scheduled in the course schedule.
Recommended or required readings
Provided in class
Assessment methods and criteria
A permanent non-certifying self-assessment is ensured during the practical exercise sessions by strong interaction between students and teachers.
The certification evaluation is carried out on the basis of the different deliverables and supports.
6 families of criteria are studied:
Field/practicals activities
Reports and deliverables
Mission-specific techniques
The different calculations and logical reasoning
The graphical report
The quality of the defense
The questions asked during the student's support are inspired by the imperfections of the different deliverables.
The evaluation criteria are: clarity, coherence, logic, rigour, precision, exhaustiveness, conciseness, relevance, transversality (within and between courses), quality of mathematical interpretations (e. g. mathematical significance of different coefficients in equations), physical (e. g. dimensions and units, order of magnitude - scaling) and geographical (single and multivariate spatial-temporal interaction and nature - type - and significance of variables - e. g.).
The critical sense of the data used (qualification, nature, meaning, representativeness, standardization, etc.) and the methodological choices (justification of the choice of methods, appropriate thresholds, etc.) will also be taken into consideration during the evaluation.
In addition, the answers will also be evaluated on the basis of the quality and originality of the graphic illustrations, and the spirit of synthesis and relevance of the different deliverables.
The final defense is the outcome of the project, and two scenarios are emerging:
Either the student demonstrates full control of the teaching unit and validates the course
Either the student presents areas for improvement on certain points which will be the subject of a second defense at the end of the quadrimester in order to rework and perfect any deficiencies
Work placement(s)
Organizational remarks
Contacts
Florent Poux, Chargé de Cours Adjoint
Unité de Géomatique, Allée du Six Août, 19
Tél. 04 366 5986
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
Remote teaching
Assessment subjects
Theory
- General understanding of massive 3D data processing methods
- Geo-data modeling, segmentation and classification
- Virtual environments
- AGILE Method
- 3D point cloud processing
- Semi-automatic and/or automatic point cloud segmentation
- Implementation of a point cloud classification method
- Establishing a complete classification of a dataset
- 3D modeling of the dataset
- Integration in a virtual environment of your choice (Virtual Tour, Virtual Reality, Augmented Reality, Mixed Reality, 3D Web Platform ...)
Assessment methods
The evaluation will be based mainly on:
- The overall methods and results of the project
- The methods and results of each sub-part
The evaluation criteria are: clarity, coherence, logic, rigor, precision, completeness, conciseness, relevance, transversality (within and between courses), quality of mathematical (e.g., mathematical meaning of different coefficients of equations), physical (e.g., dimensions and units, order of magnitude - scaling) and geographic (e.g., mono and multivariate spatial and temporal interaction and nature - type - and meaning of variables) interpretations.
Criticality with regard to the data used (qualification, nature, significance, representativeness, standardization, etc.) and methodological choices (justification of the choice of methods, appropriate thresholds, etc.) will also be taken into account during the evaluation.
In addition, the answers will also be evaluated on the basis of the quality and originality of the graphic illustrations, and the spirit of synthesis and relevance of the various deliverables.
The final defense is the outcome of the project, and two scenarios are possible:
Either the student demonstrates his total mastery of the teaching unit, and validates the course Either the student presents areas for improvement on certain points which will be the subject of a second presentation at the end of the semester in order to rework and perfect any shortcomings.
Contacts
Florent Poux, Chargé de Cours Adjoint
voir carnet d'addresse ULiege
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
see Adaptation des engagements pédagogiques suite à la pandémie de COVID-19 pour la session de mai-juin
Assessment methods
see Adaptation des engagements pédagogiques suite à la pandémie de COVID-19 pour la session de mai-juin
Contacts
fpoux@uliege.be - Tel 5986