Computational Photography

Learn about the basics of how computation has impacted the entire workflow of photography, from how images are captured, manipulated and collaborated on and shared.

About the Course

This course is aimed at teaching you the basics of how computation has impacted the entire workflow of photography, from how images are captured, manipulated and collaborated on and shared. At the core of it photography means, drawing with light and how light can be captured to form images/videos. In this class you will learn about how the optics, and the sensor within a camera are generalized, as well as the lighting and other aspects of the environment are generalized to capture novel images. We will also cover post and pre processing techniques to manipulate and improve images. Finally, we will consider the power of the web and the Internet for both analyzing and sharing images, as well as the impact of mobile smart phone cameras. This class builds on concepts from well known disciplines like computer vision, computer graphics, and image processing. Look forward to your participation in this class.

About the Instructor(s)

Irfan Essa is a Professor in the School of Interactive Computing (iC) of the College of Computing (CoC), and Adjunct Professor in the School of Electrical and Computer Engineering, Georgia Institute of Technology (GA Tech), in Atlanta, Georgia, USA. Irfan Essa works in the areas of Computer Vision, Computer Graphics, Computational Perception, Robotics and Computer Animation, Machine Learning, and Social Computing, with potential impact on Video Analysis and Production (e.g., Computational Photography & Video, Image-based Modeling and Rendering, etc.) Human Computer Interaction, and Artificial Intelligence research. His specific research interests are in Video Analysis & Synthesis, and Activity & Behavior Recognition. He also works in the new area of Computational Journalism. Specifically, he is interested in the analysis, interpretation, authoring, and synthesis (of video), with the goals of building aware environments & supporting healthy living, recognizing & modeling human behaviors, empowering humans to effectively interact with each other, with media & with technologies, and developing dynamic & generative representations of time-varying streams.
He has published over 150 scholarly articles in leading journals and conference venues on these topics. He has been awarded the NSF CAREER Award and within GA Tech, and he has won the College of Computing’s Junior and Senior Research Faculty Awards, Outstanding Teacher Award, Outstanding Mentor Award, Institute’s Educational Innovation Award, and the Dean’s Award. He is also a recipient of the GVU Center’s 15 years of Impact Award. He was elected to the grade of IEEE Fellow in 2011. He joined GA Tech Faculty in 1996 after his earning his MS (1990), Ph.D. (1994), and holding research faculty position at the Massachusetts Institute of Technology (Media Lab) [1988-1996]. His Doctoral Research was in the area of Facial Recognition, Analysis, and Synthesis.

Recommended Background

College level Math, including Linear Algebra and some programming.

Suggested Readings

No text book is required for this class, however, we will cover some material from the free, online textbook Computer Vision: Algorithms and Applications by Richard Szeliski. Additional readings will be also made available for various topics.

Course Format

The class will have lecture videos, which are between 5 and 12 minutes in length. The course will consist of four/five projects, with programming requirements.

FAQ

• Will I get a certificate after completing this class?

  Certificate of Completion will be provided by Georgia Tech C21U

• What resources will I need for this class?

  You will need access to a camera.

Provided by:

University: Georgia Institute of Technology

Instructor(s): Irfan Essa