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Seminar in Geometric Computing

Code 11513
Year 1
Semester S1
ECTS Credits 6
Workload OT(15H)
Scientific area Informatics
Mode of delivery - Face-to-face and brainstorming.
Work placements - N/A.
Learning outcomes - To introduce the postgraduates into the broad field of geometric computing.
- To educate the postgraduates with strong skills in scientific research methodologies.
- To educate the postgraduates for a research career or an academic career in geometric computing. - To be able to implement at least a reconstruction algorithm from a cloud of points generated by a 3D scanner.
- To be able to implement at least a segmentation algorithm for triangle meshes.
- To be able to distinguish an intrinsic shape descriptor from an extrinsic shape descriptor.
- To be able to implement at least an algorithm for molecular shape complementarity analysis.
- To be able to develop and implement at least a 3D biomedical segmentation algorithm.
- To be able to develop and implement at least an innovative algorithm for shape analysis.
Syllabus Triangle meshes. Reconstruction of triangle meshes, parametric surfaces, and implicit surfaces (LS, RBF, and MPU) from clouds of points. Multi-resolution meshes. Subdivision surfaces. Shape descriptors. Shape similarity. Shape registration. Shape segmentation. Industrial applications.
Main Bibliography - A. Bronstein et al., “Numerical Geometry of Non-Rigid Shapes”, Springer-Verlag, 2008.
- Warren and H. Weimer, “Subdivision Methdos for Geometric Design”, Morgan Kaufman, 2002.
- N. Dodgson et al., “Advances in Multiresolution for Geometric Modelling”, Springer-Verlag, 2005.
- A. Gomes, I. Voiculescu, J. Jorge, B. Wyvill, and C. Galbraith, “Implicit Curves and Surfaces: Mathematics, Data Structures, and Algorithms”, Springer-Verlag, 2009.
- S. Jia and J. Li, “3D Shape Analysis: Construction, Classification and Matching”, VDM Verlag, 2008.
Planned learning activities and teaching methods - theoretical classes (20%);
- roundtable discussions (60%);
- labs & project tutoring (20%)
Metodologias de Ensino e Critérios de Avaliação - 5 trabalhos de investigação sobre sobre algoritmos geométricos de dificuldade média, o que inclui a implemetação de cada um deles. (5 x 2 valores = 10 valores; 50%)
- 1 trabalho final de vulto, que pretende funcionar como o motor para a criação de novo conhecimento. (10 valores; 50%)
Language Portuguese. Tutorial support is available in English.
Last updated on: 2014-08-07

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