Semester.ly

Johns Hopkins University | EN.601.661

Computer Vision

3.0

credits

Average Course Rating

(3.95)

This course provides an overview of fundamental methods in computer vision from a computational perspective. Methods studied include: camera systems and their modelling, computation of 3¬D geometry from binocular stereo, motion, and photometric stereo, and object recognition, image segmentation, and activity analysis. Elements of machine learning and deep learning are also included. Required course background: Intro to Programming, Linear Algebra & prob/stats

Spring 2023

(3.81)

Spring 2023

(3.74)

Spring 2023

Professor: Craig Jones

(3.81)

Spring 2023

Professor: Kapil Katyal

(3.74)

Lecture Sections

(01)

No location info
K. Katyal
16:30 - 19:00

(02)

No location info
K. Katyal
16:30 - 19:00

(03)

No location info
G. Hager
13:30 - 14:45