15-463, 15-663, 15-862
Computational Photography, Fall 2018
Time: Mondays, Wednesdays 12:00 PM - 1:20 PM
Location: GHC 4102
Instructor: Ioannis (Yannis) Gkioulekas
Teaching Assistant: Alankar Kotwal
Course Description

Computational photography is the convergence of computer graphics, computer vision and imaging. Its role is to overcome the limitations of the traditional camera, by combining imaging and computation to enable new and enhanced ways of capturing, representing, and interacting with the physical world.

This advanced undergraduate course provides a comprehensive overview of the state of the art in computational photography. At the start of the course, we will study modern image processing pipelines, including those encountered on mobile phone and DSLR cameras, and advanced image and video editing algorithms. Then we will proceed to learn about the physical and computational aspects of tasks such as 3D scanning, coded photography, lightfield imaging, time-of-flight imaging, VR/AR displays, and computational light transport. Near the end of the course, we will discuss active research topics, such as creating cameras that capture video at the speed of light, cameras that look around walls, or cameras that can see through tissue.

The course has a strong hands-on component, in the form of seven homework assignments and a final project. In the homework assignments, students will have the opportunity to implement many of the techniques covered in the class, by both acquiring their own images of indoor and outdoor scenes and developing the computational tools needed to extract information from them. For their final projects, students will have the choice to use modern sensors provided by the instructors (lightfield cameras, time-of-flight cameras, depth sensors, structured light systems, etc.).

Cross-listing: This class is cross-listed as 15-463 (for undergraduate students), 15-663 (for Master's students), and 15-862 (for PhD students). Please make sure to register for the section of the class that matches your current enrollment status.


This course requires familarity with linear algebra, calculus, programming, and doing computations with images. In particular, either of the following courses can serve as proof that you satisfy these prerequisites:

If you have not taken any of the above courses but want to enroll, please contact the instructor — exceptions will be made on a case-by-case basis. The course does not require prior experience with photography or imaging.


Readings will be assigned from the following textbook (available online for free):

Additional readings will be assigned from relevant papers. Readings will be posted at the last slide of each lecture.

The following textbooks can also be useful references but are not required:


Your final grade will be made up from:

Homework assignments: All homework assignments will have a programming component and a photography component, where students will use a DSLR camera to capture and process their own images. The programming component of all assignments be done in Matlab. The first assignment will serve as a short tutorial in Matlab and DSLR cameras. We have collected a few useful Matlab resources here.

Late days: For the homework assignments, students will be allowed a total of six free late days. Any additional late days will each incur a 10% penalty. Each homework may not be submitted more than four days late.

Collaboration policy: Students are encouraged to work in groups but each student must submit their own work. This includes: writing your own code, building your own imaging setups, taking your own photographs, and producing your own writeup. If you work as a group, include the names of your collaborators in your writeup. You absolutely should not share or copy code. Additionally, you should not use any external code unless explicitly permitted. Plagiarism is strongly prohibited and will lead to failure of this course.

Final project: Details about the final project are available here.

15-663, 15-862: Students taking 15-663 or 15-862 will be required to do a more substantial final project, as well as submit a longer paper describing their project.

Submitting homeworks: We use Canvas for submitting and grading homeworks.


Students are highly encouraged to obtain a digital camera for use in the course. Any digital camera with manual controls should work. A few cameras will be provided by the instructors.

Email, Office Hours, and Discussion

Email: Please use [15463] in the title when emailing the teaching staff!

Office hours: Teaching staff have regular office hours at the following times.

Feel free to email us about scheduling additional office hours.

Discussion: We use Piazza for class discussion and announcements.

(Tentative) Syllabus

Slides will be updated on this website after each lecture.

M, Aug 27Introductionpdf, pptx
W, Aug 29Digital photography pipelinepdf, pptx
F, Aug 31HW1 out
M, Sep 3No class (Labor Day)
W, Sep 5Pinholes and lensespdf, pptx
M, Sep 10Photographic optics and exposurepdf, pptx
W, Sep 12High dynamic range imagingpdf, pptx
F, Sep 14HW1 due, HW2 out
M, Sep 17Tonemapping and bilateral filteringpdf, pptx
W, Sep 19Colorpdf, pptx
M, Sep 24Image compositingpdf, pptx
W, Sep 26No class
F, Sep 28HW2 due, HW3 out
M, Oct 1Guest lecture: Ravi Teja Mullapudipdf
W, Oct 3Gradient-domain image processingpdf, pptx
M, Oct 8Focal stacks and lightfieldspdf, pptx
W, Oct 10Deconvolutionpdf, pptx
F, Oct 12Camera models and calibrationpdf, pptx
F, Oct 12HW3 due, HW4 out
M, Oct 15Guest lecture: Anat Levinpdf1/pdf2, pptx1/pptx2
W, Oct 17Two-view geometrypdf, pptx
M, Oct 22Radiometry and reflectancepdf, pptx
W, Oct 24Photometric stereopdf, pptx
F, Oct 26HW4 due, HW5 out
M, Oct 29Light transport matricespdf, pptx
W, Oct 31Computational light transportpdf1/pdf2, pptx1/pptx2
M, Nov 5Stereo and structured lightpdf, pptx
W, Nov 7Guest lecture: Hanbyul Joopdf
S, Nov 11HW5 due, HW6 out
M, Nov 12Time-of-flight imagingpdf, pptx
W, Nov 14Non-line-of-sight imagingpdf, pptx
M, Nov 19Fourier opticspdf, pptx
W, Nov 21No class (Thanksgiving)
M, Nov 26Guest lecture: Aswin Sankaranarayananpdf, pptx
W, Nov 28No class (fire alarm)
F, Nov 30Monte Carlo rendering 101pdf, pptxHW7 out
M, Dec 3 No class
W, Dec 5Wrap-up and discussionpdf, pptx
F, Dec 7HW6 and HW7 due
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Special Thanks

These lecture notes have been pieced together from many different people and places. Special thanks TBD.