EECE 5639 — Computer Vision

4 semester hoursGraduateLectureusually offered: fall, springtypical days: T/FBostonOnlineSeattle, WATraditionalVideo Streaming

Introduces topics such as image formation, segmentation, feature extraction, matching, shape recovery, dynamic scene analysis, and object recognition. Computer vision brings together imaging devices, computers, and sophisticated algorithms to solve problems in industrial inspection, autonomous navigation, human-computer interfaces, medicine, image retrieval from databases, realistic computer graphics rendering, document analysis, and remote sensing. The goal of computer vision is to make useful decisions about real physical objects and scenes based on sensed images. Computer vision is an exciting but disorganized field that builds on very diverse disciplines such as image processing, statistics, pattern recognition, control theory, system identification, physics, geometry, computer graphics, and learning theory. Requires good programming experience in Matlab or C++.

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 2023161638%10.0
Spring 20241607382%13.0
Fall 20241133043%17.0
Fall 20251123040%18.0
Spring 202625917234%56.5

Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.

Meeting times

Share of recent sections by weekday: M 0% · T 61% · W 37% · Th 21% · F 77%

Common patterns: TF (40% of sections), WF (37% of sections), TR (21% of sections), async (2% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Percentages are each professor's average share of the season's enrolled students in recent terms.

Links

Official catalog (EECE course descriptions) · Student reviews on RateMyHusky · All EECE courses · Plan it at numap.app