This is the Windows app named WiFi DensePose whose latest release can be downloaded as wifi-denseposesourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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WiFi DensePose
DESCRIPTION
wifi-densepose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. Its architecture emphasizes performance and reproducibility, allowing developers to explore non-visual motion capture systems using accessible hardware. Overall, wifi-densepose functions as an advanced research-grade toolkit for WiFi-based human sensing and pose estimation.
Features
- WiFi-based dense pose estimation
- Real-time full-body tracking
- Works through walls and obstacles
- Commodity router compatibility
- Machine learning inference pipeline
- Live pose visualization support
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/wifi-densepose.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
