CSE 252A: Computer Vision I

Course Information

Instructor

David Kriegman
Office: EBU3B, Room 4120
Phone: (858) 822-2424
Email: kriegman at cs.ucsd.edu
Office Hours: Wednesday 3:00 – 4:00 pm, Thursday 3:30 - 4:30 pm

Teaching Assistants

Shashank Shastry (scshastr@eng.ucsd.edu)
Office Hours: Monday 10:30 - 12:00 pm B270A
Gautam Nain (gnain@eng.ucsd.edu)
Office Hours: Tuesday 2:30 - 4:00 pm B270A
Kushagra Chauhan (kchauhan@eng.ucsd.edu)
Office Hours: Wednesday 11:00 - 12:30 pm B260A
Yuan Qi (yuq083@eng.ucsd.edu)
Office Hours: Thursday 1:30 - 3:00 pm B270A

Class Description

Comprehensive introduction to computer vision providing broad coverage including low level vision (image formation, photometry, color, image feature detection), inferring 3D properties from images (shape-from-shading, stereo vision, motion interpretation) and object recognition. A companion course, CSE252B, Computer Vision II is taught in the winter quarter.

Grading

There will be five homeworks and a final exam. The assignments will contain written questions and questions that require Python programming.

• Homeworks: 65% (5% for the first one and the other four 15% each)
• Final Exam: 35% (Friday, 12/14 7:00PM-10:00PM)

Piazza

We will be using Piazza as our class web board. You'll be able to ask the professor, the TAs and your classmates questions on Piazza. Class announcements will be made using Piazza, so be sure to check your email or Piazza frequently.

Podcasts

We will try to make podcasts available for the class, but make no guarantees due to potential technical difficulties. It is highly encouraged that you still attend lectures in real life so we don't get lonely.

Required Textbook

"Computer vision: A Modern Approach," (2nd ed.) David A. Forsyth, Jean Ponce, Prentice Hall, ISBN: 013608592X

Supplemental Textbook

“Computer Vision: Algorithms and Applications”, Richard Szeliski, is available at: http://szeliski.org/Book/.

Prerequisites

Linear algebra and Multivariable calculus (e.g., Math 20A & 20F), programming, data structure/algorithms (e.g., CSE100). Probability can also be useful.

Programming

Assignments will include both written problem sets and programming assignments in Python.

Late Policy

Programming assignments will have a submission procedure described with the assignment, and has a 10% per day late penalty up to 3 days.

Collaboration Policy

You may work together on homework assignments to discuss ideas and methods only, however what you turn in should be your own work and any code should be your own coding. Copying is not permitted.

Academic Integrity

In this course we expect students to adhere to the UC San Diego Integrity of Scholarship Policy. This means that you will complete your work honestly, with integrity, and support and environment of integrity within the class for which you are tutoring.

Assignments

All assignments must be submitted on Gradescope as a single pdf file. Written problems may be typeset or hand written and scanned (but must be legible). Programming problems should be done in the provided ipython notebooks and exported (including outputs and figures) as a pdf. In addition to the pdf you must also submit the .ipynb file.

Homework 0

HW 0, HW0.pdf
Due On: Tuesday, October 9, 2018 11:59pm

Homework 1

HW 1, HW1.pdf
Due On: Tuesday, October 23, 2018 11:59pm

Homework 2

HW 2, HW2.pdf
Due On: Thursday, November 8, 2018 11:59pm

Homework 3

HW 3, HW3.pdf
Due On: Tuesday, November 20, 2018 11:59pm

Homework 4

HW 4, HW4.pdf
Due On: Friday, December 7, 2018 11:59pm

Syllabus

Note that this Syllabus is tentative & subject to change

Week	Date	Lec #	Lecture
0	9/27	1	Intro to Computer Vision, RS. 1-18
1	10/2	2	Human Visual System
1	10/4	3	Projective Geometry, Camera models, Linear algebra review
2	10/9	4	Homography, Lenses
2	10/11	5	Rigid transformations and homography
3	10/16	6	Radiometry, reflectance and lights, F&P Chapter 4; Supplemental reading Glassner Chapter 13 (requires campus network connection)
3	10/18	7	Radiometry, BRDF, Shading
4	10/23	8	Photometric stereo
4	10/25	9	SUV color space and filtering Supplementary Reading - Beyond Lambert: Reconstructing Specular Surfaces Using Color
5	10/30	10	Filtering and Edge Detection
5	11/1	11	Edge and Corner Detection, Stereo
6	11/6	12	Stereo Vision
6	11/8	13	Stereo Vision
7	11/13	14	Motion : Infinitesimal structure from Motion, Trucco and Verri pp. 195-202, 208-211 , Trucco and Verri, pp. 178-194
7	11/15	15	Motion : Tracking, F&P Chap.17, RS 235-237, 282-284, 551-552, 605-609
8	11/20	16	Visual Tracking and Recognition, F&P 326
9	11/27	17	Deep Networks 1
9	11/29	18	Deep Networks 2
10	12/4	19	Color; F&P, Chap. 6, RS 8-89, Some on-line sources include: Basics of Color, A FAQ on Color
10	12/6	20	-

Resources

Additional references

Linear algebra review
Random variables review
Sample Final Questions

Getting help

• Our class web board on Piazza is the first place to look for answers to questions and to ask questions. If you have a question, it is likely that other students do to, and so whether you’re the first or the tenth with the question, we recommend heading to Piazza first.
• Office hours: The TA’s have office hours Monday-Thursday and the Professor has office hours too.
• The IDEA Engineering Student Center, located just off the lobby of Jacobs Hall, is a hub for student engagement, academic enrichment, personal/professional development, leadership, community involvement, and a respectful learning environment for all. The Center offers a variety of programs, listed in the IDEA Center Facebook page at and the Center website. The IDEA Center programs support both undergraduate students and graduate students.

Diversity and Inclusion

We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives and experiences, and respects your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create a diverse and inclusive learning environment where all students feel comfortable and can thrive.
Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know, either in person, via email/discussion board, or even in a note under the door. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.
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 to build an environment where everyone is respected and feels comfortable.
If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination.

Students with Disabilities

We aim to create an environment in which all students can succeed in this course. If you have a disability, please contact the Office for Students with Disability (OSD), which is located in University Center 202 behind Center Hall, to discuss appropriate accommodations right away. 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 their AFA letters to Faculty (please make arrangements to contact me privately) and to the OSD Liaison in the department in advance so that accommodations may be arranged.

Basic Needs/Food Insecurities

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