ipl-uw/RT-POSE
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark (ECCV 2024)
This project helps researchers and engineers develop and test systems that can track human movement and posture without using cameras, which can be important for privacy or when optical systems are obstructed. It takes raw 4D radar sensor data as input and produces estimated 3D human skeleton positions. This is intended for professionals working in fields like ambient assisted living, smart surveillance, or human-computer interaction where privacy-preserving motion tracking is crucial.
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Use this if you need to develop or evaluate methods for tracking 3D human pose using radar sensors, especially when privacy is a concern or through-wall recognition is desired.
Not ideal if your application requires extremely high precision human pose estimation and privacy concerns are not a limiting factor, as optical systems generally offer higher accuracy.
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Python
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Last pushed
Sep 10, 2024
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