Computer vision, broadly speaking, is a research field aimed to enable computers to process and interpret visual data, as sighted humans can. It is one of the most exciting areas of research in computing science and among the fastest growing technologies in today’s industry. This course provides an introduction to the fundamental principles and applications of computer vision (see topics).
Prerequisite: All of MATH 200, MATH 221 and either (a) CPSC 221 or (b) all of CPSC 260, EECE 320.
Instructor: Jim Little (little [at] cs.ubc.ca).
Classes; MWF 1200-1250 online
Tuesdays 4pm (Zoom through Canvas)
or by appointment
TA: Kalli Leung (kalli.leung [at] alumni.ubc.ca)
Office hours: Monday 4-5pm (Zoom through Canvas)
TA: Gabriel Huang (gabrie20 [at] cs.ubc.ca)
Office hours: Wednesday 7-8pm (Zoom through Canvas)
TA: Ariel Shann (shannari [at] cs.ubc.ca)
Office hours: Thursday 5-6pm (Zoom through Canvas)
TA: Wonho Bae (whbae [at] cs.ubc.ca)
Office hours: Friday 6pm (Zoom through Canvas)
TA: Rayat Hossain (rayat137 [at] cs.ubc.ca)
Office hours: as needed
Here is a rough schedule and tentative list of topics and readings (subject to change).
|First Day of Classes||11 January (Monday)|
|Add/Drop Deadline||22 January (Friday)|
|Drop with W Deadline||12 March October (Friday)|
|Midterm Exam||March 5 in class (see below)|
|Last Day of Classes||14 April (Friday)|
|Final Exam||Tentative: 830am April 24; consult exam for official time|
The midterm will be an in-class, closed-book exam lasting 50 minutes. We will use the Lockdown Browser in Canvas. Download and install the browser before starting the exam. The midterm will be available between 1200pm and 1250pm.
The final exam will be an closed-book exam lasting 2.5 hours. We will use the Lockdown Browser in Canvas. Download and install the browser before starting the exam. The midterm will be available between 830am and 1100am on April 24th.
Mondays, Wednesdays and Fridays, 4:00pm-450pm, DMP ???
We will post the lecture materials here.
|Jan. 11||Introduction||Lecture 1|
|Jan. 13||Image Formation||Lecture 2|
|Jan. 15||Image Formation||Lecture 3|
|Jan. 18||Image Filtering||Lecture 4|
|Jan. 20||Image Filtering||Lecture 5|
|Jan. 22||Image Filtering||Lecture 6|
|Jan. 25||Sampling||Lecture 7|
|Jan. 27||Sampling||Lecture 8|
|Jan. 29||Scaled Representations||Lecture 9|
|Feb. 1||Local Image Features||Lecture 10|
|Feb. 3||Local Image Features||Lecture 11|
|Feb. 5||Edges/Boundaries||Lecture 11b|
|Feb. 8||Corners||Lecture 12|
|Feb. 10||Corners, Harris, Scale||Lecture 14|
|Feb. 12||Textures||Lecture 15 about Asst. 2||Lecture 15|
|Feb. 22||Texture Analysis||Lecture 16||Feb. 24||Colour||Lecture 17|
|Feb. 26||Colour (cont) and Local Image Features SIFT||Lecture 18|
|Mar. 1||SIFT (cont)||Lecture 19|
|Mar. 3||Object Detection||Lecture 20|
|Mar. 8||Hough Transform - Model Fitting||Lecture 21|
|Mar. 10||Hough Transform Applications||Lecture 22|
|Mar. 12||Stereo||Lecture 23|
|Mar. 15||Stereo (cont), Optical Flow||Lecture 23 cont.|
|Mar. 17||Optical Flow||Lecture 24|
|Mar. 19||Optical Flow, Classification||Lecture 25|
|Mar. 22||Classsification (cont), Image Classification||Lecture 25cont|
|Mar. 24||Classification||Lecture 26|
|Mar. 26||Classification||Lecture 27|
|Mar. 29||Object Detection||Lecture 28|
|Mar. 31||NNs||Lecture 29|
|Apr. 7||CNNs||Lecture 30|
|Apr. 9||CNNs||Lecture 31||See Piazza regarding recording of Lecture 31. Having Canvas problems|
|Apr. 12||CNNs||Lecture 32|
|Apr. 14||Groupings||Lecture 33|
There are SEVEN assignments given throughout the term. The first is a self-study tutorial introduction to Python for computer vision (that is not marked). The other six are handed in to be marked. Information about assignments will appear in Canvas.
Assignment due dates for future assignments are tentative.
|Assignment 0||No due date (but try to complete it by Jan. 18)|
|Assignment 1||Due 1159pm Friday Jan. 29|
|Assignment 2||Due 1159pm Friday Feb. 12|
|Assignment 3||Due 1159pm Monday Mar. 1|
|Assignment 4||Due 1159pm Friday Mar. 19|
|Assignment 5||Due 1159pm Wednesday Mar. 31 EXTENDED to Thurs. Apr. 1|
|Assignment 6||Due 1159pm Wednesday Apr. 14|
There will be one midterm and one final exam (see important dates)
Information about grading is in Canvas.
The course uses the following textbook, which is recommended (but not required):
Another useful textbook (which can be downloaded from http://szeliski.org/Book/) is:
Here is another one which can also be freely downloaded as a PDF from SpringerLink, through UBC Library (must login using CWL).
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