The goal of Computer Vision is to compute properties of the world from digital images. Problems in this field include recovering 3D shapes, estimating motion and object recognition, all through analysis of images and video. This course provides an introduction to image analysis and computer vision, including topics such as feature detection, motion estimation, image mosaics and 3D vision.
- Light, color and images
- Filtering, resampling, edges and corners
- Feature description and matching, Image Warping, Ransac, Panoramas
- 3D Vision : Stereo
- Deep Learning
- Dense Matching and MultiView Stereo
- Structure from Motion
- Image Based Rendering
- Graph Cut
These topics will be discussed in terms of algorithms and mathematical tools. The applications may be developed in python or C++.
Evaluation: 5 Labs + 1 project
Language: Lectures in English, Labs in English or French
- Teaching coordinator: Bredif Mathieu
- Teaching coordinator: Kalogeiton Vicky
- Teaching coordinator: Lutzeyer Johannes
- Teaching coordinator: Rohmer Damien