MoveNet

The MoveNet model is an efficient, real-time human pose estimation system designed for detecting and tracking keypoints of human bodies. It utilizes deep learning to accurately locate 17 key points across the body, providing precise tracking even with fast movements. Optimized for mobile and embedded devices, MoveNet can be integrated into applications for fitness tracking, augmented reality, and interactive systems.

Features

Real-time human pose estimation with high accuracy.
Detects 17 key points across the human body.
Optimized for mobile and embedded devices with low latency.
Suitable for fitness tracking, augmented reality, and interactive applications.
High efficiency with minimal computational resource requirements.
Works seamlessly with TensorFlow Lite for mobile deployment.
Capable of tracking fast movements with high precision.
Pre-trained model for easy integration into applications.
Provides keypoint location information for dynamic pose analysis.

Project Activity

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License

Apache License V2.0

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Additional Project Details

Registered

2025-03-19

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