course-details-portlet

TBA4256 - 3D Digital modelling

About

New from the academic year 2020/2021

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Approved exercises 30/100
Written examination 70/100 4 hours C

Course content

The working principle of LiDAR, error sources and calibration. LiDAR data preprocessing: noise filtering of point clouds, strip adjustment, and (ICP and SLAM based) registration. Classification and segmentation by using rule-based methods, RANSAC, and conditional random Field (CRF). Objects detection and recognition from 3D point clouds, especially to detect individual trees from airborne Laser Scanning data and terrestrial Laser Scanning data for the purpose of tree biometrics and biomass estimation, and façade objects (doors and windows) detection. Data structures and data formats for 3D city modelling, i.e. CityGML.

Learning outcome

Knowledge:
The candidate should have knowledge of:
- the working principle of a laser scanner, the classifications and parameter settings, the error sources and calibrations,
- the differences of laser scanning and photogrammetry,
- the data format and characteristics of Laser scanning point clouds,
- the process of data preprocessing including noise filtering, strip adjustment and data registration,
- principles and algorithms of classifications and segmentations, and the object detection as well.

Skills:
The candidate is able to:
- process the raw data acquired directly from an airborne laser scanner and terrestrial laser scanner,
- model fittings by using RANSAC or improved RANSAC, merge point clouds acquired from UAV borne and terrestrial laser scanner by using different registration methods,
- adapt and apply filters from digital image process for 3D point clouds,
- detect buildings, trees, street lights and power lines from 3D point clouds,
- and modelling the detected objects in CityGML.

General competence:
The candidate can:
- understand the relations and transformations among different coordinate system induced by the sensors (GNSS, INS, Laser transmitter, scanner),
- classify 3D point clouds into several classes (bare earth, cars, buildings and other man-made objects, power lines, pole-like objects), and segment the 3D point clouds of a building into individual plane or curved facets and model them in 3D either by using data-driven method or model-driven method,
- generate CityGML data files for the 3D objects,
- understand and use professional terminology within the discipline
- work independently and in team and take the necessary initiatives
- identify common fields between this discipline and other professional disciplines and be open for inter disciplinary approach and cooperation.

Learning methods and activities

Lechures. Computations and laboratory excersises. The lectures and assignments are in English when students who do not understand Norwegian take the course.

Compulsory assignments

  • Exerecises

Further on evaluation

Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam (70%) and evaluation of one exercise (30%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may be changed from written to oral. For a re-take of an examination, all assessments during the course must be re-taken

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Course materials

G. Vosselman and H. Maas: Airborne and terrestrial Laser Scanning.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 3
Lab hours: 2
No.of specialization hours: 7

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Geomatics
  • Geodesy
  • Nautic
  • Photogrammetry/Remote sensing
  • Photogrammetry
  • Map subjects
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Civil and Environmental Engineering

Phone:

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD Approved exercises 30/100
Room Building Number of candidates
Autumn ORD Written examination 70/100 C
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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