Moses - Automatic Image Analysis

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2017 - WS 2017/18. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40345 / #4

Validity:
SS 2017 - WS 2017/18

Default display language:
English

Module title:
Automatic Image Analysis

Credits:
6

Responsible person:
Hellwich, Olaf

Grading:
benotet

Type of exam:
Schriftliche Prüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Technische Informatik und Mikroelektronik

Area of expertise:
34341600 FG Computer Vision and Remote Sensing

Prüfungsausschuss:
No information

Kontakt

Office:
MAR 6-5

Contact person:
Hellwich, Olaf

E-mail address:
olaf.hellwich@tu-berlin.de

Website:

https://www.tu.berlin/cv

Learning Outcomes

The students acquire stepwise competence for the development of image understanding methods. According to computer vision paradigm knowledge-based image analysis methods are developed based on feature extraction. The module clarifies that the learned skills can be used within multifaceted application areas of automatic image understanding.

Content

Visual cognition, grouping, shape descriptors, computer vision paradigm, knowledge-based image analysis, models of the real world, formal representation of the models, modelling of uncertainty (softcomputing), invariant pattern recognition, Bayesian decision theorem, Markoff random field models, Bayesian networks, object categorisation, automatic interpretation of maps, application to close range and air photographs

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Automatic Image Analysis	VL	0433 L 130	SoSe	No information	2
Automatic Image Analysis	UE	0433 L 131	SoSe	No information	2

Workload and Credit Points

Automatic Image Analysis (VL):

Workload description	Multiplier	Hours	Total
Attendance	15.0	2.0h	30.0h
Preparation/ Post-processing	15.0	2.0h	30.0h
			60.0h(~2 LP)

Automatic Image Analysis (UE):

Workload description	Multiplier	Hours	Total
Attendance	15.0	2.0h	30.0h
Preparation/ Post-processing	15.0	6.0h	90.0h
			120.0h(~4 LP)

The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

The lecture explains methods and algorithms, their underlying philosophy, as well as mathematical foundations from a rather theoretical point of view. Participants are expected to rehearse topics after class in preparation for the exercises. The exercises take place in parallel. They rehearse methods and algorithms from a more practical point of view, introduce variations and extensions, and discuss implementation details of the homework assignments. Homework assignments are given during the exercises and must be solved within two weeks. These assignments cover theoretical questions as well as programming exercises and are solved by working in small groups of three to four students.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Knowledge according module „Digital Image Processing" or equivalent is preferable.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Written exam

Language

English

Duration/Extent

90 minutes

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Sommersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Registration for the exam has to be made online.

Recommended literature
http://www.cv.tu-berlin.de/menue/lectures/summer_term/automatic_image_analysis/parameter/en/

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

This module is used in the following Degree Programs (new System):

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.

Nebenhörerinnen / Nebenhörer können an der Veranstaltung teilnehmen.

Miscellaneous

The module is offered each summer term.

Automatic Image Analysis