DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
UNIVERSITY OF CALIFORNIA, SAN DIEGO

CSE 291: Topics in Computer Science and Engineering
Computational Photography

Spring 2020

Syllabus

Instructor: Ben Ochoa
Email: bochoa at ucsd.edu
Office hours: M 8:00 PM-9:00 PM (secondary) and W 8:00 PM-9:00 PM (primary), and at other times by appointment

TA: Karen Lucknavalai
Email: klucknav at eng.ucsd.edu
Office hours: M 3:00 PM-4:00 PM and W 4:00 PM-5:00 PM

Note: when emailing the instructor or TA with questions about the class, please put "CSE 291" in the subject line.

Class section ID: 5752 (must be taken for 4 units)
Lecture: MW 6:30 PM-7:50 PM
Class discussion: Piazza

Computational photography overcomes the limitations of traditional photography using computational techniques from image processing, computer vision, and computer graphics. This course provides a comprehensive introduction to computational photography and the practical techniques used to overcome traditional photography limitations (e.g., image resolution, dynamic range, and defocus and motion blur) and those used to produce images (and more) that are not possible with traditional photography (e.g., computational illumination and novel optical elements such as those used in light field cameras). Upon completion of this course, students will have an understanding of both traditional and computational photography.

Students enrolled in this course are required to complete assignments and a project, including two project presentations. When presenting to the class, follow the presentation guidelines provided by Professor Charles Elkan. If you would like your slides reviewed (highly recommended) prior to presentation to the class, then at least three days prior to your presentation date, send a draft of your slides to the instructor and TA for review. The instructor and TA will provide you with comments to incorporate into your slides prior to your presentation in class. Immediately after your presentation, send the slides (pdf, one slide per page) to the instructor. The slides for the second presentation will be published on the class website. After your presentations to the class, you will receive feedback from the instructor and TA.

All projects will follow specific guidelines, including preparation of a project proposal, draft project report, and final project report. The project need not necessarily advance the state of the field. For example, replicating the results of an innovative paper would be a good project. Projects must be closely inspired by one or two specific high quality papers and should have an experimental aspect. Project reports will be evaluated using these grading criteria.

Prerequisites: Linear algebra, calculus, and optimization. MATLAB, Python, or other programming experience.

Assignments will be prepared using LaTeX or Markdown. Programming aspects of the assignments will be completed using various programming languages.

Academic Integrity Policy: Integrity of scholarship is essential for an academic community. The University expects that both faculty and students will honor this principle and in so doing protect the validity of University intellectual work. For students, this means that all academic work will be done by the individual to whom it is assigned, without unauthorized aid of any kind.

Collaboration Policy: It is expected that you complete your academic assignments on your own and in your own words and code. The assignments have been developed by the instructor to facilitate your learning and to provide a method for fairly evaluating your knowledge and abilities (not the knowledge and abilities of others). So, to facilitate learning, you are authorized to discuss assignments with others; however, to ensure fair evaluations, you are not authorized to use the answers developed by another, copy the work completed by others in the past or present, or write your academic assignments in collaboration with another person.

If the work you submit is determined to be other than your own, you will be reported to the Academic Integrity Office for violating UCSD's Policy on Integrity of Scholarship. In accordance with the CSE department academic integrity guidelines, students found committing an academic integrity violation will receive an F in the course.


Grading: Course grades will be weighted as follows.

Assignments: 50%
Initial project presentation: 10%
Final project presentation: 10%
Project report: 30%

Late Policy: Assignments will have a submission procedure described with the assignment. Assignments submitted late will receive a 15% grade reduction for each 12 hours late (i.e., 30% per day). Assignments will not be accepted 72 hours after the due date. If you require an extension (for personal reasons only) to a due date, you must request one as far in advance as possible. Extensions requested close to or after the due date will only be granted for clear emergencies or clearly unforeseeable circumstances. You are advised to begin working on assignments as soon as they are assigned.

Assignments:

Readings:

Lecture topics (tentative):

Links:

Helpful textbooks:

Computer Vision: Algorithms and Applications
Richard Szeliski
Springer, 2011
[Amazon] [Google]

Multiple View Geometry in Computer Vision, 2nd edition
Richard Hartley and Andrew Zisserman
Cambridge University Press, 2004
[Cambridge Books Online] [Amazon] [Google]

Digital Image Processing, 4th edition
Rafael C. Gonzalez and Richard E. Woods
Pearson, 2018
[Amazon]

Schedule:

Date Lecture topic Slides
Mar 30 Overview Lecture 1
Apr 1 Cameras and image processing Lecture 2
Apr 6 Image processing Lecture 3
Apr 8 Burst photography Lecture 4
Apr 13 Burst photography Lecture 5
Apr 15 Burst photography, and camera and image motion Lecture 6
Apr 20 Computational illumination Lecture 7
Apr 22 Camera arrays and light field photography Lecture 8
Apr 27 Computational imaging Lecture 9
Apr 29 Multiscale image representations and image fusion Lecture 10
May 4 Group meetings with instructor and TA
May 6 Group meetings with instructor and TA
May 11

Initial project presentations

Riley Hadden

Dominique Meyer and Pranav Verma

Yujing Shen

Kunyu Wang

Owen Jow

May 13

Initial project presentations

Suhrid Subramaniam and Michael Liu

Lana Gaspariani and Joseph Li

Renjie Shao and Hongyi Ling

Yuhan Zhang

Ronald Allan Baldonado

May 18 Group meetings with instructor and TA
May 20 Group meetings with instructor and TA
May 25 No meeting (Memorial Day Observance)
May 27 Group meetings with instructor and TA
Jun 1

Final project presentations

Yuhan Zhang

Renjie Shao and Hongyi Ling

Lana Gaspariani and Joseph Li

Suhrid Subramaniam and Michael Liu

Jun 3

Final project presentations

Owen Jow

Kunyu Wang

Yujing Shen

Dominique Meyer and Pranav Verma

Riley Hadden

Projects:

Group members Project
Suhrid Subramaniam and Michael Liu Spherical Mosaicing
Lana Gaspariani and Joseph Li Mosaicing Artifact Removal for Planar Mosaics
Dominique Meyer and Pranav Verma 3D Mapping with an EPI Light-field Camera Array
Renjie Shao and Hongyi Ling Full-Frame Hyperlapse Video
Owen Jow Mobile Low-Light Photography
Riley Hadden Image Synthesis with Autocalibration
Yujing Shen Shift-invariant Blind Motion Deblur
Kunyu Wang Environment Matting and Compositing
Yuhan Zhang Tone Mapping with Bilateral Filtering

Diversity and Inclusion

We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives, and experiences while respecting your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create an inclusive learning environment where all students can feel comfortable and thrive. Accordingly, the instructional staff will make a concerted effort to be welcoming and inclusive to the wide range of students in this course. If there is some way we can help you feel more included, please let one of the course staff know (in person, via email/Piazza, or even using an anonymous note).

We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community. Please understand that others' backgrounds, perspectives, and experiences may be different than your own, and help us build an environment where everyone is welcomed and respected.

If you experience any sort of harassment or discrimination, please contact an instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office for the Prevention of Harassment and Discrimination.

Students with Disabilities

We aim to create an environment in which all students can succeed. If you have a disability, please contact the Office for Students with Disabilities (OSD) and discuss appropriate accommodations as soon as possible. We will work to provide you with the accommodations you need, but you must first provide a current Authorization for Accommodation (AFA) letter issued by the OSD. You are required to present your AFA letters to the instructor and to the department's OSD Liaison so that accommodations may be arranged.

Basic Needs/Food Insecurities

If you are experiencing any insecurities related to basic needs (food, housing, financial resources), there are resources available on campus to help, including The Hub and the Triton Food Pantry. Please visit The Hub for more information.


Last update: June 1, 2020