WIAS course: Image and Video Analysis

Course schedule

Dates Start time End time Location Coordinator registrations
app/max		    
11/10/2021
5 day course, 11,12, 14, 18, 21 October 2021
 09:00 17:30 Wageningen Campus Paddy Haripersaud 28 / 28 Add to waiting list

Course description

Learning goals: After finishing the course, participants will be able to:

  • Have an overview of the available image and video analysis techniques;
  • Make well-informed choices on image and video analysis techniques;
  • Manage the pitfalls originating from the images, annotation process or analysis technique.

The target group / group size: In-depth course intended for post-graduates / 20 to 30 participants.

Prior knowledge required: Some basic experience in python and digital image/video processing is required.  A self-study introduction is available if needed.

Homework: There will be some practical home assignments.

Other course information: The in-person course duration is 5 days and the course is given once per year. There will be maximally 8 hours of self-study involved. Credit points: 1.6 ECTS.

Teacher: Joy Sun, Gert Kootstra and Helena Russello

Price description: €225 for WIAS and other WGS PhD candidates; €450 for WUR staff and PhD candidates from other universities;  €675 for NGO participants; €1350 for private sector participants.

Course programme

Day

Activity

One: 11 October
  • Introduction
  • Overview of image and video analysis
  • Making good images (lab exercise)
  • Noise filtering, image pre-processing
  • Lab exercise: set up programming environment including Anaconda, OpenCV, and Spyder

Two: 12 October

 
  • Well-established computer vision techniques for feature extraction (e.g. PCA, Gabor filter)
  • Conventional machine learning methods
  • Lab exercise: feature extraction and classification

Three: 14 October

 
  • 1 hour Q&A about homework
  • Image classification (some theory on neural network types)
  • Image segmentation, conventional
  • Image segmentation, deep learning

Four: 18 October
  • Object Detection (bounding box predictions)
  • Motion detection and analysis
  • Lab exercise: Motion estimation
  • Annotation tool for object detection (CVAT)
  • Lab exercise on CVAT and object detection in videos

Five: 21 October

 
  • 1-2 hours Q&A about homework and appeared questions
  • Lecture on general image analysis pipeline control, what is not covered by individual topics
  • Invited speakers
  • Networking event, drinks