Pose Estimation to Detect People in Scenes | Fritz

Pose Estimation

Pose Estimation identifies and tracks a person's body position. By using the Vision API, app developers can build AI-powered coaches for sports and fitness, immersive AR experiences, and more.
 

Premium Available

Pose estimation is included in the free Basic plan. Upgrading to Premium adds these additional features and limits:

  • Multi-pose: track multiple people
  • Lower-latency models
  • Unlimited devices

View Plans

Detect 17 Body Parts

Coordinates for 17 keypoints and body parts are provided for each skeleton detected.

Our mobile-friendly model was trained on COCO, a large-scale pose dataset. Predicts body parts such as:

Customize Poses

Our team can create custom Pose Estimation models upon request.

Runs On-Device

All predictions / model inferences are made completely on-device.

No internet connection is required to interpret images or video.

No internet dependency means super-fast performance.

Cross-Platform SDKs

Supported mobile platforms:

  • Android Pose Estimation
  • iOS Pose Estimation
Live Video Performance

Runs on live video with a fast frame rate.

Exact FPS performance varies depending on device, but it is possible to run this feature on live video on modern mobile devices.

Technical Specifications

Architecture

Uses a MobileNet backbone

Model Size

~5 MB

FLOPS

2,500 M

Input

353x257-pixel image

Output

Position of each person and body part detected

Number of people detected

The confidence associated with each detection

Formats

Core ML, TensorFlow, TensorFlow Mobile, TensorFlow Lite, Keras

Benchmarks

20 FPS on iPhone X

5 FPS on Pixel 2