![]() This model that is part of our unified body-segmentation API can have higher accuracy across the upper body as shown in the animation below, but may be less accurate for the lower body in some situations.īoth of these new models could enable a whole host of creative applications orientated around the human body that could drive next generation web apps. The second model we are releasing is Selfie Segmentation that is well suited for cases where someone is directly in front of a webcam on a video call (<2 meters). ![]() It’s well suited for bodies in full view further away from the camera accurately capturing the feet and legs regions for example. This model is part of our unified pose-detection API offering that can perform full body segmentation and 3D pose estimation simultaneously as shown in the animation below. Today we are launching two new highly optimized body segmentation models that are both accurate and fast as part of our updated body-segmentation and pose APIs in TensorFlow.js.įirst is the BlazePose GHUM pose estimation model that now has additional support for segmentation. With the rise in interest around health and fitness, we have seen a growing number of TensorFlow.js users take their first steps in 2021 with our existing body related ML models, such as face mesh, body pose, and hand pose estimation. ![]() Posted by Ivan Grishchenko, Valentin Bazarevsky, Ahmed Sabie, Jason Mayes, Google ![]()
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