Computer vison for animal scientists: tracking and pose estimation

Course schedule

This course is not scheduled yet.

Course description

During the Image analysis course, the foundation was laid for classical and modern computer vision techniques. During this continuation course we will go deeper into two image analysis techniques which are relevant for animal scientists: tracking and pose estimation.

List course objectives

After the course you will:

  • Be able to select tracking and pose estimation computer vision techniques that are relevant for your research question and the data available.
  • use these techniques responsibly, making use of the power of computer vision while avoiding the pitfalls.
  • Understand and master computer vision-based methods for object tracking and pose estimation.
  • Be able to apply the techniques to real applications, starting from preparing the input data, to model training, and eventually evaluate the model performance.

General Information

Target Group

PhDs and postdocs and others using image analysis techniques

Course level

In-depth, post graduate

Group size

A minimum of 15 and a maximum of 30 participants

Course duration

3 days given once every two years

Prior knowledge

WIAS course: Image & Video Analysis

Home work/ self- study




Credit points


Name lecturer(s)

Gert Kootstra ( and Joy Sun (

Teaching method

Lectures, practicums and discussion groups


Wageningen University campus, Wageningen, the Netherlands.
Note: Room and building will be communicated to registered and confirmed participants about one week before the start of the course.



Day 1: Monday, 10 October: Animal pose estimation.

9:00 - 9:30        Lecture - Introduction to animal-pose estimation

9:30-11:00        Practical - Loading data, annotating data, using a U-net

11:15-12:00      Lecture - Different pose estimation deep nets

12:00-13:00      LUNCH

13:00-14:30      Practical - Working with a pose-estimation network

14:45-15:15      Lecture – From pose to gait and posture

15:30-17:00      Practical - Some applications of pose estimation

Day 2: Wednesday, 12 October: Animal tracking

9:00-9:30         Lecture - Conventional methods for object tracking, and introduction to  deep learning-based methods

9:45-11:00        Practical: - Getting the input data ready

11:15-12:00      Lecture - Deep neural networks for object detection and tracking

12:00-13:00      LUNCH

13:00-14:30      Practical - Training a neural network for object detection and tracking

14:30-15:30      Lecture - Evaluation methods and further analysis for object tracking

15:30-17:00      Practical - Evaluation and analysing of tracking results

Day 3, Thursday 13 October: Discuss your project and social activities

Afternoon:  Discuss your own project

The course students will be put in small groups together with other PhD students from WUR and Tue with a background in computer vision and deep learning. Goal is to discuss the projects of the course students and to take one to work out in more detail. The session will end with a plenary presentation of the result of each group.

Afternoon: Social activity + drinks


1) Reduced fee: WUR PhD candidates doing a Training and Supervision Plan (TSP)


2) University fee: All other PhD candidates / postdocs and staff of Wageningen University


3) External fee: All other participants


Fee includes study and training material, coffee/tea and lunches.

Cancellation condition

You may cancel free of charge up to 1 month before the start of the course. After this date you will be charged with the University fee. Unless: 

  • You can find someone to replace you in the course and supply the course coordinator with the name and contact information of your replacement. In this case you will be charged a €50,- cancellation fee.
  • You are a PhD of Wageningen University with a valid reason to cancel (illness or death in the family 1st or 2nd degree). In this case you will be charged the reduced fee and your supervisor/PI must send a mail indication the reason for cancellation.


For more information please contact:, tel: +31317486836 or