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Computational Vision (CMPT 412)

Type
Undergraduate Studies
Institution
SFU
Professor / Instructor
Yasutaka Furukawa
Dates
September 8, 2021 - December 6, 2021

Computer vision is the process of automatically extracting information from images and videos. The course covers various aspects of Computer Vision, for example, imaging geometry (camera calibration, stereo, and panoramic image stitching), video analysis (motion detection and tracking), image segmentation, object recognition, and more. The course teaches both traditional techniques and more recent learning-based approaches such as deep neural networks, while we will focus increasingly more on the latter. The course will be based on lectures and assignments (Python and Matlab). Computational approaches to image understanding will be discussed in relation to theories about the operation of the human visual system and with respect to practical applications in robotics. Topics will include edge detection, shape from shading, stereopsis, optical flow, Fourier methods, gradient space, three-dimensional object representation and constraint satisfaction.

You are applying for a $500 scholarship towards a qualifying course at one of our post-secondary education partners: BCIT, Northeastern University, SFU or UBC. Applicants must be either Canadian Citizens, BC permanent residents or working towards obtaining one of these.

Please only apply for this scholarship once you have been enrolled or waitlisted in an applicable course. We will be confirming all student details with instructors.

Apply for Scholarship

To be eligible for this scholarship, you must be a woman (or identify as a woman), and currently live in BC, Canada. Do you meet both of these criteria?