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.

Prerequisites: Upper-division standing in Electrical Engineering, Computer Engineering, Computer Science, Chemical Engineering or Mechanical Engineering.

4

Units

Letter

Grading

1, 2, 3

Passtime

Upper division only

Level Limit

Engineering

College
These majors only cheme cmpen cmpsc cpsci ee me
BEYELER M
Michael Beyeler
5.0
6 reviews
NH 1109
W
09:00 AM - 09:50 AM
12 / 13

NH 1109
W
10:00 AM - 10:50 AM
11 / 11 Full

NH 1109
W
11:00 AM - 11:50 AM
12 / 13

GIRV 2128
W
12:00 PM - 12:50 PM
12 / 13

Winter 2025 . Wang Y F
BUCHN1920
T R
12:30 PM - 13:45 PM
Fall 2025 . Manjunath B S
HFH 1104
M W
15:30 PM - 16:45 PM
See All
ECE 181 Beyeler M Fall 2024 Total: 42
ECE 181 Beyeler M Fall 2022 Total: 51
6
5.0
CS181 . Beyeler M 7 Months Ago

Class had 3 programming assignments with EC and optional HW assignments. Programing assignments were pretty useless but HW is necessary because they're just like the exams. Exams are super long and focus on very minor details so you must know everything. Prof is really nice and lectures were interesting and easy to follow. Super organized class.

0 helpful 0 unhelpful
CS181 . Beyeler M 4 Years Ago

This class had multiple choice exams and the programming assignments were easy, and lowest scores are dropped. You get to learn introductory computer vision topics and it is a fun experience overall.

2 helpful 0 unhelpful
CS165A . Beyeler M 1 Year, 1 Month Ago

Don't see how anyone could have any complaints about this guy.

0 helpful 0 unhelpful
CS165A . Beyeler M 1 Year, 4 Months Ago

A fantastic professor who explains the requirements well. He is knowledgeable in his field and helps students understand and explore outside of lectures. The class is graded mainly on projects and tests. Homework is optional in this class.

0 helpful 0 unhelpful
PSY130 . Beyeler M 4 Years Ago

I love professor Beyeler! Hes super nice and his lectures are very clear. His expectations for what you need to know is very clear as well. He made visual neuroscience very fun and interesting!

2 helpful 0 unhelpful
PSY130 . Beyeler M 4 Years Ago

Great course! Enthusiastic lecturer

0 helpful 0 unhelpful
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