Video-based analysis of animal behaviour#

Overview#

This will be an introductory course on analysing animal behaviour from video data. The course will cover:

  • Motivation

  • Overview of animal tracking methods and terminology

  • Pose estimation and tracking

    • Overview of existing tools

    • Labeling animal body parts

    • Training a model

    • Predicting poses

    • Evaluating performance

  • Analysing pose tracks with Python

    • Loading and saving data

    • Filtering/smoothing

    • Visualising tracks

    • Time spent in regions of interest

Training and prediction with pose estimation models are GPU-intensive tasks. Since many students will not have access to a GPU on their own machine, we highly recommend that they also attend the follow-up course on Running pose estimation on the SWC HPC system. This will cover how to run pose estimation at scale, using the GPUs of the SWC HPC cluster.

Prerequisites#

Make sure to follow the steps outlined here which will guide you through setting up your laptop, installing the required software, and downloading the sample data.

If you encounter issues with any of these steps please contact Niko Sirmpilatze in advance of the course. You may also drop by our office hours at the SWC Library (5th floor) on Friday Nov 24th, 13:30-16:00.

Materials#

Useful links:

Recommended readings: