CSS 587 – Advanced Topics in Computer Vision – Spring 2018
University of Washington, Bothell – School of STEM – Computing & Software Systems
Professor: Dr. Clark F. Olson Class: T/Th 5:45-7:45 pm, UW2 - 340
Office: UW1 – 271B Office Hours: T/Th 4:30-5:30 pm
Phone: (425) 352-5288 or by appointment
Lab: UW1-310 Lab tutor schedule – see https://www.uwb.edu/qsc/schedule/css
This is a project-oriented course to introduce students to computer vision research. An overview of computer vision and discussion of fundamental techniques will be presented. Students are expected to read and understand current research papers. Teams of students will implement (and potentially extend) computer vision algorithms using an open source computer vision library (OpenCV). Each team will lead a discussion on the topic of their project. The projects will culminate with demonstrations at the end of the quarter.
Topics and Learning Objectives
Textbook (optional, but recommended)
You might also consider:
· Daniel Lelis Baggio, et al., Mastering OpenCV3, Packt Publishing, 2017.
· Prateek Joshi, David Millan Escriva, and Vinicius Godoy, OpenCV By Example, Packt Publishing, 2016.
Assignments / Grading
Students will complete three introductory assignments and a substantial course project. They will lead discussion in their topic area and present their work to the class. A student who achieves 80% of the possible points should expect to receive a successful grade in the course.
Assignments: 25% Project: 45% Presentations: 20% Participation: 10%
Assignments are due prior to class on the due date. The submission site will mark assignments as late promptly at the start of class. Assignments (except presentations and demonstrations) can be turned in up to 5 days late (including weekends) with a 10% grade reduction per day. Introductory assignments are to be completed independently. Please be very careful to adhere to the student code of conduct:
Tentative Schedule (subject to change)
See also: School of STEM Course Policies