This course provides a comprehensive introduction to computer vision, starting from digital Image analysis (filtering, image pyramids, frequency based processing, Hough transform and invariant feature extraction), advancing to geometry based computer vision (2D transforms, homographies, camera models and stereo), and ending with the presentation of state-of-the-art deep learning based computer vision techniques (convolutional networks, vision transformers, object detection and semantic segmentation).