Free Course
Computational Photography
by
Offered at Georgia Tech as CS 6475
Nanodegree Program
Artificial Intelligence
Expand Your Knowledge of Artificial Intelligence
Accelerate your career with the credential that fast-tracks you to job success.
About this Course
This class explores how computation impacts the entire workflow of photography, which is traditionally aimed at capturing light from a 3D scene to form a 2D image. A detailed study of the perceptual, technical and computational aspects of forming pictures, and more precisely the capture and depiction of reality on a (mostly 2D) medium of images is undertaken over the entire term. The scientific, perceptual, and artistic principles behind image-making will be emphasized, especially as impacted and changed by computation.
Topics include the relationship between pictorial techniques and the human visual system; intrinsic limitations of 2D representations and their possible compensations; and technical issues involving capturing light to form images. Technical aspects of image capture and rendering, and exploration of how such a medium can be used to its maximum potential, will be examined. New forms of cameras and imaging paradigms will be introduced.
Course Cost
Free
Timeline
Approx. 4 months
Skill Level
intermediate
Included in Product
Rich Learning Content
Interactive Quizzes
Taught by Industry Pros
Self-Paced Learning
Student Support Community
Join the Path to Greatness
This course is your first step towards a new career with the Artificial Intelligence Program.
Free Course
Computational Photography
by
Enhance your skill set and boost your hirability through innovative, independent learning.
Course Leads
Irfan Essa
Instructor
David Joyner
Instructor
Arpan Chakraborty
Instructor
What You Will Learn
lesson 1
Introduction
- What is Computational Photography?
- Dual Photography
- Panorama
lesson 2
Digital Imaging
- Point Processes, Smoothing
- Blending Modes, Convolution and Cross-Correlation
- Gradients and Edges
lesson 3
Cameras
- Lenses
- Exposure
- Sensor
lesson 4
Comp Vision to Comp Photo
- Fourier Transform
- Blending
- Pyramids
lesson 5
Applications
- Panorama
- HDR
- Time Lapse
lesson 6
Light Field
- Lightfield
- Lightfield Camera
lesson 7
Blue / De-Blur
- Lucy-Richardon Blur
- Flutter Shutter
lesson 8
Video
- Video
- Video Textures
- Video Stabilization
lesson 9
Closing Thoughts
Prerequisites and Requirements
Students should be familiar with:
- College-level linear algebra and calculus: Knowledge of matrices, vectors, differentiation and integration, although the focus will be more on understanding and applying mathematical structures - not necessarily deriving your own;
- Physics: Vectors, optics;
- Probability theory: Distributions, density functions.
Programming assignments for this course can be completed either using Python-OpenCV (recommended platform) or Matlab/Octave. Working knowledge of either Python or Matlab would thus be required.
See the Technology Requirements for using Udacity.
Why Take This Course
You will undertake a hands-on approach over the entire term using computational techniques, merged with digital imaging processes to produce photographic artifacts. In addition to understanding how various elements of the computational photography pipeline function together to produce novel - and sometimes stunning - results, you will be given ample opportunity to appreciate and critique artifacts produced/curated by your peers.