The computer vision course is composed be three session: 1) Introduction to Image Processing and Computer Vision, 2) Visual Tracking and 3) Computer vision for augmented reality. Validating session 1 is necessary before sessions 2) and 3). Several topics are commun between sessions 2) and 3).  Slides are mainly in english. Practical courses in matlab are mainly in french and in python are in english. 

Please download this tuto (or read the last section of this page) to start the Virtual Machine Mecatronique and select the right virtual environment (for python based practicals)

Introduction to Image Processing and Computer Vision

Course outline: 

Lecture1: Introduction (download slides)  

Lecture2: Image Processing (part1): (download slides)

Lecture3: Image Processing (part2): (download slides)


Lecture4: detectors and descriptors: (download slides)

  • Interest Point Detector and Descriptor:
  • Download Practical Course (Harris detector, matlab) 

Lecture5: Geometry (download slides)



Download orientation estimation practical course (Matlab: fr)

Download additionnal images for practical course (volants) (retines)(fibres) (billes1bulles2)


Visual Tracking :

 Course outline: 

 Computer Vision for Augmented Reality

 Course outline:


Practical courses use C++ OpenCv library: Download a Visual C++ 2010 project skeleton configured for opencv (x86). 

Using python for computer vision on mecatronique virtual machine. 

Once you are logged into the virtual machine (ubuntu 16.04), launch a terminal are run the command: 

conda activate opencv

This command activates the virtual environment opencv (all libraries you need for parcticals)

the string (opencv) will appear in the beginning of the prompt command line.

If you want to use the IDE spyder, type spyder&  in the command line to launch it in a background process. 

If you want an external display of the figure, you should modify the parameters of spyder to set the execution mode to "run in an external console". You may also use your own editor (emacs, vim) and run the python script using the command: python with the name of your python script. 


Td Filtrage Spatial et Morpho Math Fr .zip [902Kb]

Uploaded Tuesday, 08 March 2016 by Super Utilisateur

TD Modeles de camera et [752.2Kb]

Uploaded Tuesday, 08 March 2016 by Super Utilisateur

Td Histogrammes et modeles [478.91Kb]

Uploaded Tuesday, 08 March 2016 by Super Utilisateur

Image Marylin echantillonnage.png [118.33Kb]

Uploaded Tuesday, 08 March 2016 by Super Utilisateur

RFIA tutoriel caffe Stefan Duffner.pdf [1.2Mb]

Uploaded Thursday, 17 November 2016 by Super Utilisateur

IMG .JPG [2.63Mb]

Uploaded Thursday, 05 January 2017 by Super Utilisateur

stade francais jpg .JPG [37.19Kb]

Uploaded Friday, 06 January 2017 by Super Utilisateur [1.37Mb]

Uploaded Thursday, 04 October 2018 by Super Utilisateur