Pose Estimation

Real-time computer vision that maps human skeletal joints and spatial orientation from standard video frames.

Pose estimation utilizes deep learning architectures like MoveNet and MediaPipe to track 17+ keypoints (shoulders, elbows, knees) at 30+ frames per second. It powers industrial safety monitors that detect falls, fitness apps that count squat repetitions, and surgical robotics requiring sub-centimeter precision. By converting raw pixels into structured coordinate data, this tech enables hardware to interpret human intent and movement without wearable sensors.

https://github.com/tensorflow/tfjs-models/tree/master/pose-detection