Course Information

Computer vision, broadly speaking, is a research field aimed to enable computers to process and interpret visual data (namely in the form of images and video), 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, including image formation, sampling and filteering, colour analysis, single and multi-image geometry, feature detection and matching, stereo imaging, motion estimation, segmentation, image classification and object detection. We'll study basic methods and application of these concepts to a variety of visual task.

Prerequisites: MATH 200, MATH 221 and either (a) CPSC 221 or (b) CPSC 260, EECE 320.

Academic Conduct: Each student is responsible for understanding and abiding by the University and Departmental policies on academic conduct. Any violations of such policies will be punishable according to the guidelines. Specifically:
- Computer Science Department Policies on Academic Integrity
- UBC policy on Academic Misconduct
- Computer Science Department Policies on Equality, Inclusion and Wellness
- Computer Science Department Policies and Responsibilities.

Textbook

Recemended (but not required):

Computer Vision: A Modern Approach (2nd edition), by D.A. Forsyth and J. Ponce, Pearson, 2012. (buy)	Computer Vision: Algorithms and Applications, by R. Szeliski, Springer, 2010. (download)

Additional Books and Materials: The following textbooks are also on reserve in the reading room.
- Concise Computer Vision: An Introduction into Theory and Algorithms, by R. Klette, Springer, London, 2014. (can be freely downloaded as a PDF from SpringeLink, through UBC Library; must login using CWL).
- Computer vision : models, learning, and inference, by S.J.D. Prince, Cambridge University Press, 2012.
- Multiple view geometry in computer vision (2nd edition), by R. Hartley and A. Zisserman, Cambridge University Press, 2003.
- Pattern classification (2nd edition), by R.O. Duda, P.E. Hart, and D.G. Stork, Wiley, 2001.

Grading

Assignments (25% of the grade)

All assignments are to be done individually. There are 5 graded (and 1 ungraded) asssignment each worth the same amount - 5% of the total grade.

Late Policy: Every student is allotted two ``late days'', which allow assignments to be handed in late without penalty on three days or parts of days during the term. The purpose of late days is to allow students the flexibility to manage unexpected obstacles to coursework that arise during the course of the term, such as travel, moderate illness, conflicts with other courses, extracurricular obligations, job interviews, etc. Thus, additional late days will NOT be granted except under truly exceptional circumstances. If an assignment is submitted late and a student has used up all of her/his late days, 25% will be deducted for every day the assignment is late. (e.g., an assignment 2 days late and graded out of 100 points will be awarded a maximum of 60 points.) How late does something have to be to use up a late day? A day is defined as a 24-hour block of time beginning at 10 minutes past the start of the lecture on the day an assignment is due. To use a late day, write the number of late days claimed on the first page of your assignment. Examples: Handing in an assignment at the end of lecture on the day it is due consumes one late day. Handing in an assignment at 10:15 the morning after it is due consumes one late day. Handing in an assignment at 2:30 the day after an assignment is due consumes two late days.

Expectations: To get top marks, programs must not only work correctly, but also must be clearly documented and easily understood. The material you hand in, including figures, must be legible.

Schedule