Computational Photography
Spring 2023
Instructor: Nima Kalantari


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Course information

Time and location: MWF 11:30 - 12:20 pm in ZACH 350
Office hours: MW 2:00 - 3:00 pm
Office location: 406 PETR
Email: nimak@tamu.edu
Campuswire: link in the syllabus

TA: Pedro Figueiredo
Email: pedrofigueiredo@tamu.edu
Office hours: TF 2:00 - 4:00 pm
Location: Peterson 402

Overview

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.

Prerequisites

Undergraduate: (CSCE 315 or CSCE 331) and (MATH 304 or MATH 311)
Graduate: Graduate students are expected to have similar background.

Textbook

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

Grading

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 Canvas 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.

Schedule*

Date Topic Slides Reading Assignments
Jan 18 Introduction and Overview pptx Szeliski Ch. 1
Jan 20 Camera and Image Formation pptx Szeliski Ch. 2.2.3 HW 1 Out
Jan 23 Camera and Image Formation See Above Szeliski Ch. 2.2.3<
Jan 25 SIGGRAPH Deadline -- No Class
Jan 27 Camera and Image Formation See Above Szeliski Ch. 2.2.3<
Jan 30 Camera and Image Formation See Above Szeliski Ch. 2.2.3< HW 1 Due
Feb 1 Class Cancelled
Feb 3 Color pptx Szeliski Ch. 2.3.2
Feb 6 Color See Above Szeliski Ch. 2.3.2 HW 2 Out
Feb 8 Sampling, Frequency, and Filtering pptx Szeliski Ch. 3.2 & 3.4
Feb 10 Sampling, Frequency, and Filtering See Above Szeliski Ch. 3.2 & 3.4
Feb 13 Sampling, Frequency, and Filtering See Above Szeliski Ch. 3.2 & 3.4
Feb 15 Sampling, Frequency, and Filtering See Above Szeliski Ch. 3.2 & 3.4 HW 2 Due
Feb 17 Pyramids pptx Szeliski Ch. 3.5 HW 3 Out
Feb 20 Image Blending pptx Szeliski Ch. 8.4.4
Feb 22 Image Blending See Above Szeliski Ch. 8.4.4
Feb 24 Image Blending See Above Szeliski Ch. 8.4.4 HW 3 Due & HW 4 Out
Feb 27 Point processing and Image Warping pptx Szeliski Ch. 3.1 & 3.6
Mar 1 Point processing and Image Warping See Above Szeliski Ch. 3.1 & 3.6
Mar 3 Point processing and Image Warping See Above Szeliski Ch. 3.1 & 3.6
Mar 6 Point processing and Image Warping See Above Szeliski Ch. 3.1 & 3.6
Mar 8 Homographies and Mosaics pptx Szeliski Ch. 8.2
Mar 10 Automatic Image Alignment and RANSAC pptx Szeliski Ch. 7.1 & 8.1 HW 4 Due
Mar 13 Spring Break -- No Class
Mar 15 Spring Break -- No Class
Mar 17 Spring Break -- No Class
Mar 20 Automatic Image Alignment and RANSAC See Above Szeliski Ch. 7.1 & 8.1 Final Project Out
Mar 22 Stereo See Above
Mar 24 Stereo pptx Szeliski Ch. 12.1 & 12.2
Mar 27 Midterm
Mar 29 Stereo See Above
Mar 31 Modeling Light and Lightfields pptx Szeliski Ch. 14.3 Proposal Due
Apr 3 Image Retargeting pptx Avidan HW 5 Out
Apr 5 Image Retargeting See Above Avidan
Apr 7 Reading Day -- No Classes
Apr 10 Image Morphing pptx Szeliski Ch. 3.6.2 & 3.6.3
Apr 12 HDR & Tonemapping pptx Szeliski Ch. 10.2
Apr 14 HDR & Tonemapping See Above Szeliski Ch. 10.2 HW 5 Due & HW 6 Out
Apr 17 HDR & Tonemapping See Above Szeliski Ch. 10.2
Apr 19 Midterm Solution
Apr 21 HDR & Tonemapping See Above Szeliski Ch. 10.2
Apr 24 Video Textures pptx Schodl HW 6 Due
Apr 26 Texture Synthesis and Filling pptx Szeliski Ch. 10.5
Apr 28 Image Analogies and Scene Completion pptx Szeliski Ch. 10.5.1 & 10.5.2
May 1 Image Analogies and Scene Completion See Above Szeliski Ch. 10.5.1 & 10.5.2

*Schedule might change during the semester.

Acknowledgements

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.