Vasek Hlavac's
teaching/tutorial presentations
(if interested in
lectures in the Czech language then click
here)
I created several teaching presentations during my teaching and writing textbooks. I like to make the material available to other teachers or students for noncommercial purposes. I try to keep updating my lectures and this gradually propagates to the teaching material. Most of my presentations are created in LaTeX and I provide the .pdf files. If an instructor intends to get a source code and images then I ask him to write me an email. Sometimes, I use Powerpoint.
I look at the web time to time to see how my other colleagues teach. I appreciate those who provide their material to the others. Sometimes, I evolve an idea seen elsewhere and include it into my presentation. I am not always able to acknowledge the original source of the idea because the ideas propagate to teaching presentations of others quickly. Allow me to express my gratitude to many of you en block for your stimuli.
I will appreciate the feedback from you, pointers to mistakes, suggestions for improvements, links to a better treatment of the topic, etc. Please, send me an email.
The numbers used as prefixes in the directory and the file names have only an auxiliary function. They help me to keep the proper ordering of directories or several presentations in the same directory. The sequence of used number is sparse by purpose to allow me to include future lectures in between if needed.
Table of contents and links:
| Image processing | |
| Lecture | File |
| I teach image processing to a huge amount of bachelor program students. My talks are mostly in Czech. If you understand it then see the Czech variant. However, I plan to convert lectures to English to provide presentations to the recently published book Sonka, Hlavac, Boyle: Image Processing, Analysis, and Machine Vision, 3rd Edition, Thomson Engineering, Toronto, Canada, April 2007. | None. |
| 04 Color imaging | |
| Image analysis, mainly 2D | |
| Lecture | File |
| 32-02 Segmentation in 2D images, taxonomy, thresholding | |
| 32-04 Segmentation in 2D images by spatial coherence | |
| 44 RANSAC | |
| 51 Objects description in 2D images | |
| 61 Physiology of the human eye | .ppt |
| 3D computer vision | |
| Lecture | File |
| 01 Introduction to 3D vision | |
| 02 Geometry of one camera | |
| 13 Geometry of two and more cameras | |
| 41 Motion in images | |
| 61 Tracking in image sequences | |
| 85 Video compression | .ppt |
| Pattern Recognition | |
| Lecture | File |
| 03 Introduction to pattern recognition | |
| 12 Bayesian approach to pattern recognition | |
| 13 Empirical evaluation of the classifier performance | |
| 15 Non-bayesian approach to pattern recognition, a few known tasks | |
| 22 Two commonly used statistical models in PR, conditional independence, Gaussian models | |
| 25 Notes on learning, 4 formulations of the classifier learning | |
| 27 Learning theory of Vapnik-Chervonentkis, estimation of the needed length of the training set | |
| 32-04 Linear classifiers | |
| 32-04 Support Vector Machines | |
| Robotics | |
| Lecture | File |
| I do not teach robotics regularly for several years. See presentations of V. Smutny who has been teaching robotics in CMP since. I mention robotics only in two lectures in computer vision course at the Faculty of Mathematics and Physics, Charles University Prague. | none |
| 11 Kinematics of Robots | |
| 61 Tele-robotics | |
Maintained by V. Hlavac,
http://cmp.felk.cvut.cz/~hlavac,
hlavac@fel.cvut.cz
Last modification
28.06.2008 05:21