Track: Animals in Motion#

Machine learning methods for motion tracking have transformed a wide range of scientific disciplines—from neuroscience and biomechanics to conservation and ethology. Tools such as DeepLabCut and SLEAP enable researchers to track animal movements in video recordings with impressive accuracy, without the need for physical markers.

However, the variety of available tools can be overwhelming. It’s often unclear which tool is best suited to a given application, or how to get started. Moreover, generating motion tracks is only the first step: these tracks must then be further processed, visualised, and analysed to yield meaningful and interpretable insights into animal behaviour.

Target audience

This course is designed for researchers and students interested in learning about the latest free open-source tools for tracking animal motion from video footage and extracting quantitative descriptions of behaviour from motion tracks.

Course overview#

Tuesday morning: We’ll start with a primer on Computer Vision approaches for detecting and tracking animals in videos. We’ll also cover key concepts and terminology, and provide an overview of the most widely used tools.

Tuesday afternoon: We’ll continue with a hands-on tutorial on using SLEAP—a popular software library for animal pose estimation and tracking. The typical workflow, from annotating body parts to training a model and generating predictions, is common to most pose estimation tools, including DeepLabCut.

Wednesday: The second day will be dedicated to a practical tutorial on movement—a Python toolbox for analysing animal body movements across space and time. You’ll learn how to load, clean, visualise, and quantify motion tracks, and apply this knowledge to specific use cases through computational exercises.

Instructors#

Pre-requisites#

Hardware#

As this is a hands-on workshop, we recommend bringing your own laptop. A mouse is also recommended for tasks like image annotation. A dedicated GPU is not required

Software#

Please ensure you have the following installed:

We will email you at least a week before the event with instructions on installing any additional required software.

Python knowledge#

If you’re new to Python, we recommend attending our Intro to Python workshop on Monday, or completing an equivalent course beforehand. This hands-on session will cover the basics, including data types, control flow, functions, and core libraries—a great way to get up to speed before this event.

Data#

Bringing your own data is encouraged but not required. This could include video recordings of animal behaviour and/or motion tracks you’ve already generated. It’s a great chance to get feedback on your data and learn from others. If you don’t have your own data, we will provide example datasets for you to work with.

We expect that participant-led ideas emerging from this track may inspire collaborative projects during the Hackday on Friday.

Apply now!#

Fill in this Google form to apply. We unfortunately have limited space to accommodate participants. To maximise our impact, we aim to select participants that would benefit the most from the event, and that can bring the experience back to a diverse set of fields. Please be specific in your application and tailor it to the main track(s) that you are planning to attend. There is funding for travel and accommodation available. Applicants will be informed of the outcome by early July.