An introduction to MediaPipe’s Face Landmarker & how it can power hands free gaming

Paul and Lance dive deep into Face Landmarker, the underlying MediaPipe task that's used for Project Gameface and dissect the code piece by piece. Paul explains how the model works to interpret extraneous movements that you can make with your face and how it protects user privacy. Learn how you can use the model to power your own creations.
Project Gameface is an open-source hands-free gaming project powered by AI that allows users to control a computer using their head movement and facial gestures. For more info, check out the first episode.
Resources:
Learn more about Project Gameface → goo.gle/3wCCaDR
Watch episode 1 → goo.gle/3WGc5yd
Watch episode 2 → goo.gle/4b77mtX
Watch episode 3 → goo.gle/3UXswVA
Chapters:
0:00 - Introduction
0:50 - Last episode recap
2:07 - What is tessellation
4:14 - Face landmarkers
6:46 - Creating the detector
7:33 - Detection results
8:37 - What is the lag?
9:01 - Highlighting the irises
9:26 - How the model is open to any face
10:38 - Open for anyone to use
Subscribe to the TensorFlow channel → goo.gle/TensorFlow
#MediaPipe #Accessibility #Gaming
Speaker: Paul Ruiz

[@james_whitford]

Amazing work

[@Cyb3r-Kun]

where can I get the code used in this video?