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AI ModelComputer Vision

Human Pose Estimation Model

A human pose estimation model is a computer vision system that detects and localizes key human body joints (keypoints) from images or video, reconstructing a person’s pose in 2D or 3D. It underpins applications like motion analysis, AR/VR, sports analytics, and human–computer interaction by turning raw pixels into structured representations of human movement.

Key Features

  • •Detection of human body keypoints (e.g., head, shoulders, elbows, wrists, hips, knees, ankles) in 2D and/or 3D
  • •Support for single-person and multi-person pose estimation in crowded scenes
  • •Real-time or near–real-time inference on video streams depending on model architecture and hardware
  • •Robustness to occlusions, varying lighting, and diverse body shapes and clothing (model-dependent)
  • •Integration with downstream tasks such as action recognition, gesture control, and motion tracking

Pricing

Unknown

Pricing depends on the specific implementation/vendor: open-source research models are typically free under their licenses, while commercial APIs and SDKs are usually paid or freemium.

Alternatives

OpenPoseBlazePose (MediaPipe)MoveNetHRNet (High-Resolution Network) for Pose EstimationAlphaPose

Industries Using Human Pose Estimation Model

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Often Used With

Computer Vision Model (1)Pose Estimation Model (1)

Quick Stats

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Total Use Cases
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Industries
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