Introduction to Computer Vision
Examine image representation (by both human brain and digital); image filtering and edge detection; keypoint detection and matching; camera model and geometric calibration; stereo vision and essential/fundamental matrices; triangulation and epipolar geometry; depth estimation; video and optical flow; classical machine learning concepts; image classification; object detection and segmentation; deep learning for computer vision (basics). Only one of the following may be counted: Electrical and Computer Engineering 371P, 379K (Topic: Computer Vision), Electrical Engineering 379K (Topic: Computer Vision). Three lecture hours a week for one semester.
Prerequisites & course information
Examine image representation (by both human brain and digital); image filtering and edge detection; keypoint detection and matching; camera model and geometric calibration; stereo vision and essential/fundamental matrices; triangulation and epipolar geometry; depth estimation; video and optical flow; classical machine learning concepts; image classification; object detection and segmentation; deep learning for computer vision (basics). Only one of the following may be counted: Electrical and Computer Engineering 371P, 379K (Topic: Computer Vision), Electrical Engineering 379K (Topic: Computer Vision). Three lecture hours a week for one semester.
Sources
- Course catalogue ↗2026-2027