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Introduction to Computer Vision
Winter Quarter 2013
Professor Matthew Turk (contact info)
Office hours: Tuesday 9:30-11:30am or by appointment, or drop by and see if I'm available (Frank Hall 2163)
TA and Reader
TA: Mathieu Rodrigue (contact), Office Hours: Thurs 3:30-5:30 (GSL) - tentative
Reader: I Ting Huang (contact)
Meeting Times and Locations
Lectures: Mon/Wed 2:00-3:15pm, Phelps 1401
Discussion session: Fri 2:00-2:50pm, Phelps 1401
Email: cs181b at cs.ucsb.edu goes to the instructor and the TA
Mailing list: http://lists.cs.ucsb.edu/mailman/listinfo/cs181b
Prerequisite: Upper-division standing
Overview of computer vision problems and techniques for analyzing the content of images and video. Topics include image formation, edge detection, image segmentation, pattern recognition, texture analysis, optical flow, stereo vision, shape representation and recovery techniques, issues in object recognition, and case studies of practical vision systems.
This course intends to provide students with a general understanding of the field of computer vision and specific techniques for processing and analyzing images. There will be a good deal of programming use C/C++ and OpenCV, so it is assumed that students are very familiar with how to program in a high-level language, how to use and link with software packages, how to use an IDE (integrated development environment) for editing, compiling, and debugging, etc. If you don't currently know C/C++ well, you may need to spend some extra time early in the quarter familiarizing yourself with C/C++ programming. No prior use of OpenCV is assumed.
Computer vision is a really interesting and timely topic, but it definitely requires a lot of hard work to master. If you put a lot into this course, I believe you will get a lot out of it!