Computer Vision

Catalog description

How can we program computers to understand the visual world? This course provides an overview to computer vision, including low-level aspects like fundamentals of image formation, feature detection and matching, camera geometry, and depth reconstruction, and higher-level semantic aspects that are made possible with deep learning including via supervised and self-supervised methods. Required: linear algebra and an introduction to AI. Recommended: probability, calculus.