This is a Computer Vision classes prepared for the 2nd-year M.D. students. Course includes topics covering basic areas of computer vision. It takes 8 seminars-discussion lessons and 8 practical lessons. Most practical lessons will be based on using of the OpenCV v3. library. All materials and tasks will be hosted in this repository and available for all students. All program code is written under Visual Studio 2015 with v120 toolset.
Please ensure you have following instruments and settings to start the work:
- CMake >=3.0
- Git
- OpenCV 3.2
- Camera to execute demo applications
- Basics of Digital Signal Processing
- Basics of Digital Image Processing
- C++ experience
- Git experience
Course consist of
- 16 seminars/practical lessons.
- 4 individual programming tasks.
| # | Date | Topic | Brief | Lab |
|---|---|---|---|---|
| 1 | 12.09.17 | Introduction | Planning | Task 1 |
| 2 | 19.09.17 | Image Segmentation (other) | Skin, K-means, Gabor filters segmentation | |
| 3 | 26.09.17 | Motion Detection | Mean, MinMax, 1G, GMM | Task 2 |
| - | cancelled | |||
| 4 | 10.10.17 | Motion Detection | Quality Assesment | |
| 5 | 17.10.17 | Feature Points | Corner Detectors (Moravec, Harris, Shi-Tomasi, FAST) | Task 3.1 |
| 6 | 24.10.17 | Feature Points | Blob Detectors (LoG, DoG, CSS) | |
| 7 | 31.10.17 | Feature Descriptors | HOG, Binary Descriptors: BRIEF, ORB, BRISK, FREAK | Task 3.2 |
| 8 | 07.11.17 | Feature Descriptors | SIFT, SURF descriptors | |
| 9 | 14.11.17 | Feature Matchers | ROC-curve, K-d Tree, Nearest Neighbor Search | Task 3.3 |
| - | cancelled | |||
| 10 | 28.11.17 | Geometric Transformations | Affine, Perspective, ICP, RANSAC | |
| 11 | 05.12.17 | Feature Tracking | Lucas-Kanade + modifications | Task 4 |
| 12 | 12.12.17 | lab checking... | ||
| 13 | 19.12.17 | Stereovision | Epipolar Geometry, Calibration, Depth Map | |
| 14 | 26.12.17 | lab checking... |
Detailed plan can be found by following link