IGFF IMA 4103
M1
Graduate
Fall
Programme Ingénieur
Français/French
3
30
75
-To master the core techniques for extracting visual and audio information.
-To understand related technological challenges and gain insight into emerging multimedia application issues.
- To master the architecture and basic capabilities of the OpenCV open-source library for computer vision and machine learning.
Aucun
The 1st session relies on continuous evaluation (CE) based on labs. Here, the final grade is the average of grades for individual lab reports.
The 2nd sessions is a written exam (WE)
The final grade is computed as: Sup (CE, Moy (CE, WE))
Supports de cours remis par les intervenants
Bibliographie :
- A. Bovik (Ed.). Handbook of Image & Video Processing. Academic Press, 2000
- L.G. Shapiro et J-C. Stockman. Computer Vision. Prentice Hall, 2001
- E.R. Davies. Machine Vision: Theory, Algorithms, Practicalities. Academic Press, 1997
- R. Jain, R. Kasturi et B.G. Schunck. Machine Vision. McGraw-Hill, 1995
- A.K. Jain. Fundamentals of Digital Image Processing. Prentice Hall, 1989
- R. Boite, H. Boulard et al. Le Traitement de la Parole. Presses Polytechniques Romandes, 2000
- A.K. Jain et R.C. Dubes. Algorithms for Clustering Data. Prentice Hall, 1988
- R. Duda, P. Hart et D. Stork. Pattern Classification (2nd edition). Wiley-Blackwell, 2000
- Bibliographie OpenCV en ligne : https://fr.pinterest.com/mediatheqtemtsp/opencv/