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Computational Photography

Georgia Institute of Technology via Coursera

students interested
The goal of this course is to introduce you to the basics of how computation has impacted the entire workflow of photography (i.e., from how images are captured, manipulated and collaborated on, and shared).  

The course begins with a conceptualization of photography as drawing with light and the capturing of light to form images/videos.  You will learn about and understand how the optics and the sensor within a camera are generalized, as well as learn about and understand how the lighting and other aspects of the environment are also generalized through computation to capture novel images. 

Pre- and post-processing techniques used to manipulate and improve images will be discussed.  Activities in this course are selected to give you first hand experience with the power of the web and the Internet for both analyzing and sharing images.  

This course is interdisciplinary and draws upon concepts and principles from computer vision, computer graphics, image processing, mathematics and optics.

We look forward to your engagement and participation with both the course and its discussion forums.

About the TA
Denis Lantsman is the TA for the class. Denis is a graduate of Harvey Mudd College, and is currently finishing his MS in Machine Learning at Georgia Tech. He is responsible for managing the coursera site, monitoring the forums for student feedback, creating the homework assignments and quizzes, as well as recording weekly tutorials to help students with their programming.

Taught by

Irfan Essa
Cost Free Online Course (Audit)
Pace Finished
Subject Programming
Provider Coursera
Language English
Certificates Certificate Available
Hours 5-8 hours a week
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MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
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Reviews for Coursera's Computational Photography
3.0 Based on 3 reviews

  • 5 star 33%
  • 4 star 0%
  • 3 star 33%
  • 2 star 0%
  • 1 star 33%

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1.0 3 years ago
by Jonathan Golland dropped this course and found the course difficulty to be very hard.
this had too much math for my taste. This isn't for me, but geared to math geniuses. Not for me!
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3.0 2 years ago
Indranil Sinharoy partially completed this course.
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5.0 2 years ago
by Colin Khein completed this course.
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