PoseNet is an open-source model for performing pose estimation on the web. Pose estimation refers to computer vision techniques that detect human figures in images and video, so that one could determine, for example, where someone’s elbow shows up in an image. To be clear, this technology is not recognizing who is in an image — there is no personal identifiable information associated to pose detection. The algorithm is simply estimating where key body joints are.

With PoseNet running on TensorFlow.js anyone with a decent webcam-equipped desktop or phone can experience this technology right from within a web browser. And since the model is open-sourced, Javascript developers can tinker and use this technology with just a few lines of code. What’s more, this can actually help preserve user privacy. Since PoseNet on TensorFlow.js runs in the browser, no pose data ever leaves a user’s computer.


Tools: Tensorflow.js

Year: 2018

Team: Dan Oved, Tyler Zhu, Tensorflow.js Team

Role: Project lead

Link: Github page, Blog post