Computational Photography
Spring 2020
Instructor: Nima Kalantari

This page has been archived and the materials are not accessible.

Course information

Time and location: MWF 10:20 - 11:10 am in 113 HRBB
Office hours: TTh 2:00 - 3:00 pm
Office location: 527B HRBB

TA: Avinash Paliwal
Office hours: MW 3:00 - 5:00 pm
Office location: EAB-C 118C


Computational photography is a collection of computational algorithms and system designs (e.g., sensors, optics) to avoid the limitations of standard cameras and enable novel applications. In recent years, there has been increasing interest in computational photography because of the widespread use of the cameras by the general public through smartphones and other cheap imaging devices. In this course, we first discuss the cameras and the image formation process. We then study basic image and video processing tools like sampling, filtering, and pyramids. Finally, we discuss several image-based algorithms, such as image retargeting, high dynamic range imaging, and texture synthesis.


CSCE 315 and MATH 304. Graduate students are expected to have similar background.


The primary reference of the course is the following book, which covers most of the topics related to computational photography:

Computer Vision: Algorithms and Applications, by Richard Szeliski, 2010


Late Submissions

You will lose 20% from each assignment for each day that it is late. However, there will be 5 granted late days for the entire course. You are free to use it for any of the assignments (note that, you CANNOT use it for the final project!). You will not get any bonuses for any of the unused late days. All the assignments are due at 11:59 pm on ecampus unless otherwise stated. Note that, one minute over and 23 hours over both count as one full day.

Academic Integrity

The assignments in this class are individual unless otherwise stated. For the individual assignments, all the codes need to be written by the student. If indicated in the assignment’s instruction, the use of external libraries for performing basic operations is allowed. However, using an outside source code is NOT permitted. Moreover, collaborating with other students on assignments beyond general discussions is NOT allowed. In general, looking at other students’ code and/or written answers is NOT allowed. If the students have any questions regarding this issue, they should contact the instructor. The students should not post their code online even after the deadline for the assignment has passed.


Date Topic Slides Reading Assignments
Jan 13 Introduction and Overview pdf, pptx Szeliski Ch. 1
Jan 15 Camera and Image Formation pdf, pptx Szeliski Ch. 2 HW 1 Out
Jan 17 SIGGRAPH Deadline - No Class See above Szeliski Ch. 2
Jan 20 MLK Day - No Class
Jan 22 Camera and Image Formation See above Szeliski Ch. 2
Jan 24 Camera and Image Formation
Jan 27 Color pdf, pptx Szeliski Ch. 2.3.2 HW 1 Due
Jan 29 Color See above Szeliski Ch. 2.3.2
Jan 31 Color See above Szeliski Ch. 2.3.2 HW 2 Out
Feb 3 Sampling and Filtering pdf, pptx Szeliski Ch. 2.3.1 & 3.2
Feb 5 Sampling and Filtering See above Szeliski Ch. 2.3.1 & 3.2
Feb 7 Frequency Domain pdf, pptx Szeliski Ch. 3.4
Feb 10 Frequency Domain See above Szeliski Ch. 3.4 HW 2 Due
Feb 12 Pyramids pdf, pptx Szeliski Ch. 3.5 HW 3 Out
Feb 14 Blending and Compositing pdf, pptx Szeliski Ch. 9.3
Feb 17 Blending and Compositing See above Szeliski Ch. 9.3
Feb 19 Point Processing and Image Warping pdf, pptx Szeliski Ch. 3.1 & 3.6.1
Feb 21 Point processing and Image Warping See above Szeliski Ch. 3.1 & 3.6.1
Feb 24 Homographies and Mosaics pdf, pptx Szeliski Ch. 9.1
Feb 26 Automatic Image Alignment and RANSAC pdf, pptx Szeliski Ch. 4.1 & 6.1.4
Feb 28 Automatic Image Alignment and RANSAC See above Szeliski Ch. 4.1 & 6.1.4
Mar 2 Stereo pdf, pptx Szeliski Ch. 11 HW 3 Due
Mar 4 Stereo See above Szeliski Ch. 11
Mar 6 Modeling Light and Lightfields pdf, pptx Szeliski Ch. 13.3 HW 4 Out
Mar 9 - 13 Spring break - No Class
Mar 16 No Class
Mar 18 No Class
Mar 20 No Class
Mar 23 Image Retargeting pdf, pptx Avidan, Rubinstein HW 4 Due
Mar 25 Image Retargeting See above Avidan, Rubinstein HW 5 Out
Mar 27 Image Retargeting See above Avidan, Rubinstein
Mar 30 Matting pdf, pptx Szeliski Ch. 10.4 & Sun
Apr 1 Image Morphing pptx Szeliski Ch. 3.6.2 & 3.6.3
Apr 3 Video Textures pptx Szeliski Ch. 13.5.2 & Schodl
Apr 6 HDR & Tonemapping pptx Szeliski Ch. 10.2 & Debevec
Apr 8 HDR & Tonemapping See above Szeliski Ch. 10.2 & Debevec HW 5 Due & HW 6 Out
Apr 10 Reading Day - No Class
Apr 13 HDR & Tonemapping See above Szeliski Ch. 10.2 & Mertens
Apr 15 Texture Synthesis and Filling pptx Szeliski Ch. 10.5
Apr 17 Image Analogies and Scene Completion pptx Hertzmann, Hays
Apr 20 Image Analogies and Scene Completion See above Hertzmann, Hays HW 6 Due
Apr 22 Coded Exposures and Apertures pptx Raskar, Levin
Apr 24 Coded Exposures and Apertures See above Raskar, Levin
Apr 27 No Class

*Schedule might change during the semester.


The slides in this class are heavily based on the slides from other instructors. Specifically, many slides are the exact or modified version of the slides by Alexei A. Efros, James Hays, and Rob Fergus, who in turn have used materials from Steve Seitz, Rick Szeliski, Paul Debevec, Stephen Palmer, Paul Heckbert, David Forsyth, Steve Marschner, Fredo Durand, Bill Freeman, and others, as noted in the slides. The instructor gives full permission to use these slides for academic and research purposes, but please maintain all the acknowlegements.