Computer Vision Systems


Bachelor: 3h/week course and 2h/week laboratory, Winter semester
Lecturer: Sorin Grigorescu
Laboratory: Sorin Grigorescu
Language: Romanian

Results February 2018


Lecture Module Description Course Materials
1 Introduction Introduction to computer vision slides
2 Image formation and color spaces
3 Filtering and Segmentation Image representation and noise slides
4 Spatial filtering
5 Template matching
6 Region segmentation slides
7 Edge detection
8 Hough transform
9 Object Recognition Linear regression slides
10 Logistic regression
11 Neural Networks
12 Convolutional Neural Networkds slides
13 Optics and 3D Reconstruction Ideal camera model slides
14 Camera calibration
15 Stereo vision slides
16 Epipolar geometry and the fundamental matrix
17 Points of interest and correspondence matching
18 Object tracking Optical flow slides
19 Dynamic models for object tracking

Laboratory work

Lab Description Lab Materials
1 Development of a computer vision application details
2 Image manipulation details
3 Thresholding details
4 Edge detection details
5 Correspondence points detection and 3D reconstruction details
6 RGB-D data processing details
7 Iterative Closest Point details
8 Cluster extraction details
9 Face detection details
10 Object tracking details


Written and practical exam at the end of the semester.