Description

This course covers the basic concepts of computer vision. This course has two parts. The first part of classical computer vision discusses camera model, image processing, corner detection, edges, interest point, image warping, homography, model fitting, stereo and optical flow. The second part of modern computer vision with deep learning includes topics for convolutional neural network, transformer network, image classification, segmentation, and object detection.

Lectures

Labs

Office hours and contact information

Topics

 

Reading list

Prerequisites

Grading