Moses - Computer Vision

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2016 - SS 2017.

Module / Version:
#40391 / #5

Validity:
SS 2016 - SS 2017

Default display language:
English

Module title:
Computer Vision

Credits:
12

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:
Dennert, Marion

E-mail address:
marion.dennert@tu-berlin.de

Website:

http://www.cv.tu-berlin.de/

Learning Outcomes

Automatic Image Analysis: 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. Digital Image Processing: Qualification aim of this module is to impart methods for signal processing, image enhancement, feature extraction and grouping. The alumni have learned and practiced to use their skills in multifaceted application areas.

Content

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS
Automatic Image Analysis	VL	0434 L130	SoSe	No information	2
Digital Image Processing	VL	0433 L110	WiSe	No information	2
Automatic Image Analysis	UE	0434 L131	SoSe	No information	2
Digital Image Processing	UE	0433 L 111	WiSe	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)

Digital Image Processing (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)

Digital Image Processing (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 360.0 Hours. Therefore the module contains 12 Credits.

Description of Teaching and Learning Methods

Automatic Image Analysis / Digital Image Processing: Underlying philosophy, methods and algorithms are explicated in the lectures. In the exercises which take place in parallel, methods and algorithms are implemented and applied exemplarily.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

For Automatic Image Analysis: Knowledge according module „Digital Image Processing" or equivalent is recommended.

Mandatory requirements for the module test application:

1. Requirement

Homework Automatic Image Analysis

2. Requirement

Homework Digital Image Analysis

Module completion

Grading

graded

Type of exam

Written exam

Language

English

Duration/Extent

90 Minuten

Duration of the Module

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

This module may be commenced in the following semesters:
Winter- und 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/
http://www.cv.tu-berlin.de/menue/lectures/winter_term/digital_image_processing/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

No information

Computer Vision