Duration
20h Th, 25h Pr
Number of credits
| Master in geography: geomatics (120 ECTS) | 3 crédits | |||
| Master in geography : geomatics and surveying (120 ECTS) | 3 crédits |
Lecturer
N...
Substitute(s)
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The "3D Recognition & Understanding" course will enable you to master the key principles related to the intelligent processing of 3D data. Your objective is to complete the course by carrying out the various missions requested, linked to a final project.
To help you realize this project, I provide you with 3 tools:
- Theoretical courses, to prepare you and allow you to rely on a clear basis
- Practical work, to directly apply theoretical learning
- Supervised support based on the deliverables of the various missions.
- 3D data and point clouds
- Python for 3D data science
- Assembly, neighbourhood and discrete differential geometry
- 3D data structures
- Feature extraction
- Segmentation of point clouds
- Point clouds classification
- Implementation for semi-automated decision-making scenarios
Learning outcomes of the learning unit
Develop tools for the automatic and intelligent processing of 3D data, specifically 3D point clouds.
Prerequisite knowledge and skills
- 3D Acquisition (GEOG0063) + 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
Assessment subjects
Assessment methods
Contacts
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
- 3D data and point clouds
- Python for 3D data science
- Assembly, neighbourhood and discrete differential geometry
- 3D data structures
- Feature extraction
- Segmentation of point clouds
- Point clouds classification
- Implementation for semi-automated decision-making scenarios
Assessment methods
The assessment will be based on:
- a complete report in response to the issues proposed in the document available on the eCampus space, and whose instructions are explicitly described (30%)
- the quality of the data deposited on the DoX space provided for this purpose (instructions in the eCampus space ) (30%)
- a video conference presentation of the results (40%)
Contacts
fpoux@uliege.be