IFD:Photography and the Machine

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Fachmodul
Photography and the Machine
Instructor: Jesús Velázquez
Credits: 6 ECTS, 4 SWS
Capacity: max. 10 students
Language: English
Date: Montag/Monday, 13:30-16:45
Location: Online
First Meeting: 11 May 2020 BISON Course ID: 320110028

Description

In the last years we have seen major changes in the way we experience, consume, produce and think of Photography.

From algorithms affecting how your selfie looks on the fly, instant filters or digital tools for editing in a couple of taps on a screen to reproducing 3D objects and places with 2D based media.

Students in this course will explore different artistic strategies, bridging technologies and topics such as photogrammetry, machine learning, computational photography, image recognition and generation, etc. in order to develop new narratives and strategies in Photography.

Admission requirements

Concurrent enrollment in another IFD course offering, or with instructor permission.

Registration Procedure

In addition to the enrollment via the BISON portal, candidates are required to send a PDF portfolio including one page motivation letter, stating your interest for the course, current competences and background at: jesus.velazquez.rodriguez[ät]uni-weimar[dot]de

Evaluation

Successful completion of the course is dependent on regular attendance, active participation, completion of assignments, delivery of a relevant semester prototype and documentation. Please refer to the Evaluation Rubric for more details.

Eligible participants

Fachmodul:
MFA Medienkunst/-gestaltung, MFA Media Art and Design, MSc MediaArchitecture

Platforms and Tools

Primary Synchronous Conferencing:
Cisco Webex
Contingency Synchronous Conferencing:
Jitsi
Zoom


Student references, links and further readings


Syllabus (subject to change)

11 May 2020 / Week 1

Introduction
Course Organization
Administrative Housekeeping


18 May 2020 / Week 2

GANs in Art
Other (computer) approaches
Sources and Links from the Lecture


25 May 2020 / Week 3

Intro to Photogrammetry
Sources and Links from the Lecture