Course unit
Computational geometry
Last updated: 22/02/2024
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Course Director(s):
GAVET Yann
General Description:
The objective of this UP is to learn the concepts and manipulate the classical tools of computational geometry to characterize, model and simulate point patterns or spatial objects distributions.
This UP is mainly composed of lectures (10,5h), tutorials using Python (10,5h). Two exams, theoretical (1,5h) and practical using Python (1,5h), will evaluate the learning of this UP.
Key words:
Point patterns
convex hull
Delaunay triangulation
alpha-shapes
statistical shape analysis
Number of teaching hours
24
Fields of study
Teaching language
French
English
Intended learning outcomes
| On completion of the unit, the student will be capable of: |
Classification level |
Priority |
Learning assessment methods
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Percentage ratio of individual assessment
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Percentage ratio of group assessment
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Written exam:
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50
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%
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Project submission:
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%
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Individual oral exam:
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%
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Group presentation:
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%
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Individual presentation:
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%
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Group practical exercise:
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50
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%
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Individual practical exercise:
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%
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Group report:
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%
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Individual report:
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%
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Other(s): %
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Programme and content
| Type of teaching activity |
Content, sequencing and organisation |
| Course |
6 lectures / 10,5h : • Polygons / Convex hull (3h) • Delaunay / Voronoï (1.5h) • Nearest Neighbors (1.5h) • Statistical Shape Analysis (1.5h) • Alpha-shapes (1.5h) • Object labelling (1.5h) |
| Supervised studies |
6 tutorials using Python / 10,5h : • Polygons / Convex hull (3h) • Delaunay / Voronoï (1.5h) • Nearest Neighbors (1.5h) • Statistical Shape Analysis (1.5h) • Alpha-shapes (1.5h) • Object labelling (1.5h) |