The video below introduces Headroid1, this face-tracking robot will grow into a larger system that can follow people’s faces, detect emotions and react to engage with the visitor.
The above system uses openCV’s face detection (using the Python bindings and facedetect.py) to figure out whether the face is in the centre of the screen, if the camera needs to move it then talks via pySerial to BotBuilder‘s ServoBoard to pan or tilt the camera until the face is back in the centre of the screen.
Update – see Building A Face Tracking Robot In An Afternoon for full details to build your own Headroid1.
Headroid is pretty good at tracking faces as long as there’s no glare, he can see people from 1 foot up to about 8 feet from the camera. He moves at different speeds depending on your distance from the centre of the screen and stops with a stable picture when you’re back at the centre of his attention. The smile/frown detector which will follow will add another layer of behaviour.
Later over coffee Danny Hope and I discussed (with Headroid looking on) some ideas for tracking people, watching for attention, monitoring for frustration and concentration and generally playing with ways people might interact with this little chap:
The above was built in collaboration with BuildBrighton, there’s some discussion about it in this thread. The camera is a Philips SPC900NC which works using macam on my Mac (and runs on Linux and Win too). The ServoBoard has a super-simple interface – you send it commands like ’90a’ (turn servo A to 90 degress) as text and ‘it just works’ – it makes interactive testing a doddle.
The following should help you move forwards:
Ian is a Chief Interim Data Scientist via his Mor Consulting. Sign-up for Data Science tutorials in London and to hear about his data science thoughts and jobs. He lives in London, is walked by his high energy Springer Spaniel and is a consumer of fine coffees.