Phelma Formation 2022

Medical imaging processing - 5PMSTIM1

  • Number of hours

    • Lectures 6.0
    • Projects 0
    • Tutorials 6.0
    • Internship 0
    • Laboratory works 8.0

    ECTS

    ECTS 2.0

Goal(s)

This course provides a comprehensive introduction to image and video processing as well as computer vision. Major topics include image transformation and alignment, image compression, feature extraction and description using 2D and 3D descriptors, object recognition, geometry-based and physics-based vision and video analysis.

Contact Dawood AL CHANTI

Content(s)

  • For the CTD sessions:
    • 2h CTD: 2D Image Transformation (Wrapping)
    • 2h CTD: Feature Detectors and Descriptors (2D and 3D) for Object Recognition
    • 2h CTD: Optical Flow Estimation
    • 2h CTD: Object Tracking
    • 2h CTD: Image Compression
    • 2h CTD: Video Compresion
  • For the BE sessions:
    • 2h BE on Image Transformation
    • 2h BE on Feature extraction and object recognition
    • 2h BE on optical flow and object tracking
    • 2h BE on Image and Video Compression


Prerequisites
  • This course requires familiarity with:
    • linear algebra
    • calculus
    • basic probability
    • programming in Python

Test

Semester 9 - The exam may be taken in french or in english FR EN

  • Session 1:
    • QCMs: 3 QCMs, each weighing 10%, so total of 30%.
    • BE: BE report, will require implementing a significant computer vision algorithm : 50%.
    • Project: group based (2 members maximum), studies and presents a method we do not cover in class: 20%.
  • Session 2:
    • BE: Redo the entire BE with an in-depth analysis and a full report: 50%.
    • EXAM: Written exam 50%.


  • N1=50%BE + 30%QCMs + 20%Project
  • N2=50%BE + 50%EXAM

Additional Information

Semester 9 - This course is given in english only EN

Course list
Curriculum->Double-Diploma Engineer/Master->Semester 9
Curriculum->Engineering degree->Semester 9

Bibliography

  • Computer Vision: Algorithms and Applications, 2nd ed. Richard Szeliski