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Irfan Essa, David Joyner, and Arpan Chakraborty

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.

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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.

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Taught by Irfan Essa, David Joyner, and Arpan Chakraborty, each of whom has done work in the course's subject matter
Explores the relationship between pictorial techniques and the human visual system, a topic highly relevant to photographers and image makers
Develops technical aspects of image capture and rendering, which are core skills for photographers
Examines new forms of cameras and imaging paradigms, which may add color to the work of photographers
Requires working knowledge of Python or Matlab, which may be known by many students in the target audience

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Reviews summary

Deep dive into computational photography

According to students, the Computational Photography course offers a strong theoretical foundation and challenging, practical programming assignments crucial for skill development. Learners appreciate its broad coverage of topics, ranging from human vision to advanced imaging paradigms, and generally find the explanations clear and concise. However, some indicate that it assumes a high level of programming proficiency and mathematical understanding, making it potentially difficult for those without solid prerequisites. The course is considered highly valuable for professionals and students aiming for a deeper dive into this technical field.
Covers a wide array of topics, offering a comprehensive overview.
"The course touches on so many interesting aspects of computational photography."
"I appreciate the breadth of topics, from human vision to new camera paradigms."
"It's a great introduction to the field with a wide range of subjects explored."
Concepts are explained effectively, making complex topics accessible.
"The instructor explains complex algorithms in a very clear and understandable way."
"I found the lectures to be well-structured and easy to follow."
"The explanations helped me grasp difficult concepts easily."
Provides a deep understanding of core computational photography principles.
"This course really helps build a strong theoretical foundation in computational photography."
"I gained a comprehensive understanding of the underlying principles, which is crucial for this field."
"The explanations of the scientific and perceptual aspects were very clear and insightful."
Features demanding programming assignments that build practical skills.
"The programming assignments are challenging but incredibly rewarding for applying concepts."
"I found the projects pushed me to really understand the material and hone my coding abilities."
"My skills in Python-OpenCV significantly improved thanks to the practical exercises."
Requires solid programming knowledge and mathematical background.
"I struggled a bit without a very strong background in linear algebra and programming."
"The course assumes a higher level of Python/Matlab proficiency than I anticipated."
"While beneficial, some of the concepts felt too advanced without prior specific knowledge."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computational Photography with these activities:
Read "Understanding Exposure" by Bryan Peterson
Reading this book will help you understand the fundamentals of exposure and how to control it to create better photographs.
Show steps
  • Read the book.
  • Take notes on the key concepts.
  • Experiment with the concepts you learned in your own photography.
Watch Photography Tutorial Videos
Watching photography tutorial videos can help you learn new techniques and improve your skills.
Show steps
  • Find a tutorial on a topic that you want to learn more about.
  • Watch the tutorial and take notes on the key points.
  • Practice the techniques you learned in your own photography.
Practice Capturing Photos in Different Lighting Conditions
Practicing capturing photos in different lighting conditions will help you learn how to adjust your camera settings to get the best possible results.
Browse courses on Lighting
Show steps
  • Find a scene with a variety of lighting conditions.
  • Take a series of photos of the scene, experimenting with different camera settings.
  • Review your photos and see how the different camera settings affected the exposure.
Four other activities
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Show all seven activities
Your First Photographic Project
Creating a photographic project is a great way to practice and implement the visual concepts and technical skills you are learning in this photography course.
Show steps
  • Choose a theme or subject for your project.
  • Create a plan for your project, including the types of images you will capture and the equipment you will need.
  • Go out and shoot your photos.
  • Edit and process your photos.
  • Share your project with others and get feedback.
Develop a Photography Essay
Creating a photography essay will help you learn to visually communicate a narrative with your photographs.
Show steps
  • Shoot your photos.
  • Brainstorm a topic for your essay.
  • Research your topic and gather visual inspiration.
  • Create a storyboard for your essay.
  • Edit and sequence your photos.
  • Write the text for your essay.
Create a Photography Portfolio
Creating a photography portfolio will help you showcase your best work and get feedback from others.
Browse courses on Photography
Show steps
  • Select your best photos.
  • Edit and process your photos.
  • Design and layout your portfolio.
  • Share your portfolio with others and get feedback.
Help Others Learn Photography
Helping others learn photography will help you solidify your own understanding of the concepts and techniques.
Browse courses on Photography
Show steps
  • Find someone who is interested in learning photography.
  • Share your knowledge and experience with them.
  • Provide feedback on their work.

Career center

Learners who complete Computational Photography will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Computational Photography.
This classic textbook provides a comprehensive overview of digital image processing, covering fundamental concepts, algorithms, and applications. It valuable resource for both students and practitioners in the field.
This textbook provides a comprehensive overview of computer vision, covering fundamental algorithms, techniques, and applications. It valuable resource for students and practitioners in the field.
Provides a comprehensive overview of the science behind photography, covering optics, light, and digital imaging. It valuable resource for students and practitioners in the field.
This textbook provides a comprehensive overview of digital image processing using MATLAB. It valuable resource for students and practitioners in the field.
This textbook provides a comprehensive overview of computer vision for computer science students. It valuable resource for students and practitioners in the field.
This textbook provides a comprehensive overview of digital image processing and analysis. It valuable resource for students and practitioners in the field.

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