This is the first guide in a series of training your own gesture recognition on the Raspberry Pi using machine learning. Although fun, you will quickly see some of the limitations of this approach:
- Changes location, background and even clothing can throw detection off.
- Recording longer example videos can cause out of memory errors during training.
- Training networks to recognise subtle gestures that don't cause a lot of visual change in the image is difficult.
You can easily extend the example code by modifying the classifier network and by changing the actions that are performed when each category is detected. If you are already familiar with neural networks I recommend adding data augmentation techniques and exploring different feature extraction networks such as larger MobileNets and the Inception family.
We will explore these topics in future guides, so look out for guides on:
- Enhancing gesture recognition - training networks to recognise gestures in many situations and how to use larger datasets.
- Teachable Pi - a set of tools for building gesture recognition into Pi-based projects, with installation and usage instructions.